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  • 1. INTRODUCTION TO WIRELESS COMMUNICATION CELLULAR AND MOBILE COMMUNICATIONCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 1 / 303
  • 2. What is Wireless Communication? Wireless communication is basically transmitting/receiving voice and data using EM waves in open space, basically free from wires.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 2 / 303
  • 3. What is Wireless Communication? Wireless communication is basically transmitting/receiving voice and data using EM waves in open space, basically free from wires. The information from the sender to the receiver is usually carried over a well defined frequency band. This frequency band also known as bandwidth allocated for wireless communication, is one of the most priced commodity.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 2 / 303
  • 4. What is Wireless Communication? Wireless communication is basically transmitting/receiving voice and data using EM waves in open space, basically free from wires. The information from the sender to the receiver is usually carried over a well defined frequency band. This frequency band also known as bandwidth allocated for wireless communication, is one of the most priced commodity. The different channels can be formed because wireless communication today is not just between one person and the base station but it is a multiple access scenario, it is a multi user system.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 2 / 303
  • 5. What is Wireless Communication? Wireless communication is basically transmitting/receiving voice and data using EM waves in open space, basically free from wires. The information from the sender to the receiver is usually carried over a well defined frequency band. This frequency band also known as bandwidth allocated for wireless communication, is one of the most priced commodity. The different channels can be formed because wireless communication today is not just between one person and the base station but it is a multiple access scenario, it is a multi user system. So we need to wisely allocate the frequency channel so that we can accommodate more than one users.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 2 / 303
  • 6. Example Assume a spectrum of 120 KHz is allocated over a base frequency for communication between station A and BCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 3 / 303
  • 7. Example Assume a spectrum of 120 KHz is allocated over a base frequency for communication between station A and B Each channel occupies 40 KHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 3 / 303
  • 8. Example Assume a spectrum of 120 KHz is allocated over a base frequency for communication between station A and B Each channel occupies 40 KHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 3 / 303
  • 9. Types of Wireless Communication Mobile → Cellular phones (GSM/CDMA 2000.1X)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 4 / 303
  • 10. Types of Wireless Communication Mobile → Cellular phones (GSM/CDMA 2000.1X) Portable → IEEE 802.11b (Wi-Fi)& IEEE 802.15.3 (UWB)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 4 / 303
  • 11. Types of Wireless Communication Mobile → Cellular phones (GSM/CDMA 2000.1X) Portable → IEEE 802.11b (Wi-Fi)& IEEE 802.15.3 (UWB) Fixed → IEEE 802.16(Wireless MAN)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 4 / 303
  • 12. Typical Frequencies FM radio → 88 MHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 5 / 303
  • 13. Typical Frequencies FM radio → 88 MHz TV Broadcast → 200 MHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 5 / 303
  • 14. Typical Frequencies FM radio → 88 MHz TV Broadcast → 200 MHz GSM Phones → 900 MHz , 1800 MHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 5 / 303
  • 15. Typical Frequencies FM radio → 88 MHz TV Broadcast → 200 MHz GSM Phones → 900 MHz , 1800 MHz PCS Phones → 1.8 GHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 5 / 303
  • 16. Typical Frequencies FM radio → 88 MHz TV Broadcast → 200 MHz GSM Phones → 900 MHz , 1800 MHz PCS Phones → 1.8 GHz Bluetooth → 2.4 GHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 5 / 303
  • 17. Typical Frequencies FM radio → 88 MHz TV Broadcast → 200 MHz GSM Phones → 900 MHz , 1800 MHz PCS Phones → 1.8 GHz Bluetooth → 2.4 GHz WiFi → 2.4 GHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 5 / 303
  • 18. Typical Frequencies FM radio → 88 MHz TV Broadcast → 200 MHz GSM Phones → 900 MHz , 1800 MHz PCS Phones → 1.8 GHz Bluetooth → 2.4 GHz WiFi → 2.4 GHz 2.4 GHz band is the most favourite band it is a licence free band. Please note that we have put 2.4 as a number, that is not the only frequency at which it works, its a frequency band all the time. We also have frequencies working at 28 GHz, 42 GHz, 60 GHz and trial runs are made at 100 GHz.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 5 / 303
  • 19. Electromagnetic SpectrumCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 6 / 303
  • 20. Why Wireless Communication?(1) Freedom from wires: There is no cost of installing wires or rewiring Global Coverage:Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 7 / 303
  • 21. Why Wireless Communication?(1) Freedom from wires: There is no cost of installing wires or rewiring No bunches of wires running here and there Global Coverage:Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 7 / 303
  • 22. Why Wireless Communication?(1) Freedom from wires: There is no cost of installing wires or rewiring No bunches of wires running here and there ”Auto magical” instantaneous communications without physical connection setup, eg; Bluetooth, WiFi Global Coverage:Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 7 / 303
  • 23. Why Wireless Communication?(1) Freedom from wires: There is no cost of installing wires or rewiring No bunches of wires running here and there ”Auto magical” instantaneous communications without physical connection setup, eg; Bluetooth, WiFi Global Coverage: Communications can reach where wiring is infeasible or costly, eg; rural areas, old buildings, battle field, vehicles, outer space(through communication satellites)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 7 / 303
  • 24. Why Wireless Communication?(2) Stay connected: Roaming allows flexibility to stay connected anywhere and any time. Flexibility:Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 8 / 303
  • 25. Why Wireless Communication?(2) Stay connected: Roaming allows flexibility to stay connected anywhere and any time. Rapidly growing market attests to public need for mobility and uninterrupted access Flexibility:Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 8 / 303
  • 26. Why Wireless Communication?(2) Stay connected: Roaming allows flexibility to stay connected anywhere and any time. Rapidly growing market attests to public need for mobility and uninterrupted access Flexibility: services reach you wherever you go (Mobility). For example you dont have to go to your lab to check your mail.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 8 / 303
  • 27. Why Wireless Communication?(2) Stay connected: Roaming allows flexibility to stay connected anywhere and any time. Rapidly growing market attests to public need for mobility and uninterrupted access Flexibility: services reach you wherever you go (Mobility). For example you dont have to go to your lab to check your mail. Connect to multiple devices simultaneously(no physical connections required)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 8 / 303
  • 28. Challenges(1) Efficient Hardware: Low power Transmitters, Receivers Efficient use of finite radio spectrum: Integrated services:Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 9 / 303
  • 29. Challenges(1) Efficient Hardware: Low power Transmitters, Receivers Low power signal processing tools Efficient use of finite radio spectrum: Integrated services:Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 9 / 303
  • 30. Challenges(1) Efficient Hardware: Low power Transmitters, Receivers Low power signal processing tools Efficient use of finite radio spectrum: Cellular frequency reuse, medium access control protocols Integrated services:Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 9 / 303
  • 31. Challenges(1) Efficient Hardware: Low power Transmitters, Receivers Low power signal processing tools Efficient use of finite radio spectrum: Cellular frequency reuse, medium access control protocols Integrated services: voice, data, multimedia over a single network.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 9 / 303
  • 32. Challenges(1) Efficient Hardware: Low power Transmitters, Receivers Low power signal processing tools Efficient use of finite radio spectrum: Cellular frequency reuse, medium access control protocols Integrated services: voice, data, multimedia over a single network. service differentiation, priorities, resource sharingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 9 / 303
  • 33. Challenges(2) Network support for user mobility(mobile scenarios)- location identification, handoverCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 10 / 303
  • 34. Challenges(2) Network support for user mobility(mobile scenarios)- location identification, handover Maintaining quality of service over unreliable linksCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 10 / 303
  • 35. Challenges(2) Network support for user mobility(mobile scenarios)- location identification, handover Maintaining quality of service over unreliable links Connectivity and coverage (inter-networking)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 10 / 303
  • 36. Challenges(2) Network support for user mobility(mobile scenarios)- location identification, handover Maintaining quality of service over unreliable links Connectivity and coverage (inter-networking) Cost efficiencyCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 10 / 303
  • 37. Challenges(3) FadingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 11 / 303
  • 38. Challenges(3) Fading MultipathCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 11 / 303
  • 39. Challenges(3) Fading Multipath Higher probability of data corruptionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 11 / 303
  • 40. Challenges(3) Fading Multipath Higher probability of data corruption Need for stronger security mechanismCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 11 / 303
  • 41. A simplified wireless communication system representationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 12 / 303
  • 42. Current Wireless Systems: Now let us look into some of the current wireless systems. Cellular systemsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 13 / 303
  • 43. Current Wireless Systems: Now let us look into some of the current wireless systems. Cellular systems Wireless LAN’sCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 13 / 303
  • 44. Current Wireless Systems: Now let us look into some of the current wireless systems. Cellular systems Wireless LAN’s Satellite systemsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 13 / 303
  • 45. Current Wireless Systems: Now let us look into some of the current wireless systems. Cellular systems Wireless LAN’s Satellite systems Paging systemsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 13 / 303
  • 46. Current Wireless Systems: Now let us look into some of the current wireless systems. Cellular systems Wireless LAN’s Satellite systems Paging systems PAN’s (Bluetooth)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 13 / 303
  • 47. UNIT 1 MULTIPLE ACCESS TECHNIQUES AND CELLULAR CONCEPTCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 14 / 303
  • 48. Unit 1: MULTIPLE ACCESS TECHNIQUES AND CELLULAR CONCEPT Multiple access schemes are generally allowed to use many mobile users share a finite amount of radio spectrum. We know that radio spectrum is a premium resource because most of the cost comes from licensing the spectrum.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 15 / 303
  • 49. Unit 1: MULTIPLE ACCESS TECHNIQUES AND CELLULAR CONCEPT Multiple access schemes are generally allowed to use many mobile users share a finite amount of radio spectrum. We know that radio spectrum is a premium resource because most of the cost comes from licensing the spectrum. The sharing of spectrum is required to achieve high capacity by simultaneously allocating the bandwidth. There are several ways to do so and hence there are several multiple access schemes. Bandwidth is one of the resource which has to be shared.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 15 / 303
  • 50. Unit 1: MULTIPLE ACCESS TECHNIQUES AND CELLULAR CONCEPT Multiple access schemes are generally allowed to use many mobile users share a finite amount of radio spectrum. We know that radio spectrum is a premium resource because most of the cost comes from licensing the spectrum. The sharing of spectrum is required to achieve high capacity by simultaneously allocating the bandwidth. There are several ways to do so and hence there are several multiple access schemes. Bandwidth is one of the resource which has to be shared. The constraint in sharing resource is that there should not be severe performance degradation.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 15 / 303
  • 51. Frequency Division Multiple Access (FDMA) One of the most important multiple access schemes is the Frequency Division Multiple Access (FDMA)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 16 / 303
  • 52. FDMACellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 17 / 303
  • 53. TDMACellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 18 / 303
  • 54. TDMACellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 19 / 303
  • 55. CDMACellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 20 / 303
  • 56. CDMACellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 21 / 303
  • 57. Terminologies Mobile: A radio terminal attached to a high speed mobile platform (eg; a cell phone in a fast moving vehicle.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 22 / 303
  • 58. Terminologies Mobile: A radio terminal attached to a high speed mobile platform (eg; a cell phone in a fast moving vehicle. Portable: A radio terminal that can be hand held and used by someone at walking speed (eg; a cordless telephone).Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 22 / 303
  • 59. Terminologies Mobile: A radio terminal attached to a high speed mobile platform (eg; a cell phone in a fast moving vehicle. Portable: A radio terminal that can be hand held and used by someone at walking speed (eg; a cordless telephone). Subscriber: A mobile or portable user.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 22 / 303
  • 60. Terminologies Mobile: A radio terminal attached to a high speed mobile platform (eg; a cell phone in a fast moving vehicle. Portable: A radio terminal that can be hand held and used by someone at walking speed (eg; a cordless telephone). Subscriber: A mobile or portable user. Base Stations: Fixed antenna units with which the subscribers communicate. Base stations are connected to a commercial power source and a backbone network.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 22 / 303
  • 61. Terminologies Cells: The area of coverage is divided into cells. Each cell has a base station located at its centre or an edge.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 23 / 303
  • 62. Terminologies Cells: The area of coverage is divided into cells. Each cell has a base station located at its centre or an edge. Control Channel: Radio channels used for transmission of call set-up, call request and call initiation.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 23 / 303
  • 63. Terminologies Cells: The area of coverage is divided into cells. Each cell has a base station located at its centre or an edge. Control Channel: Radio channels used for transmission of call set-up, call request and call initiation. Forward channel(downlink):Radio channel used for transmission of information from the base station to the mobile.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 23 / 303
  • 64. Terminologies Cells: The area of coverage is divided into cells. Each cell has a base station located at its centre or an edge. Control Channel: Radio channels used for transmission of call set-up, call request and call initiation. Forward channel(downlink):Radio channel used for transmission of information from the base station to the mobile. Reverse channels(uplink):Radio channel used for transmission of information from the mobile to the base station.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 23 / 303
  • 65. Terminologies Full Duplex Systems: Simultaneous two way communication. Transmission and reception on two different channels.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 24 / 303
  • 66. Terminologies Full Duplex Systems: Simultaneous two way communication. Transmission and reception on two different channels. Hand-off: The process of transferring the mobile station from one channel or base station to another.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 24 / 303
  • 67. Terminologies Full Duplex Systems: Simultaneous two way communication. Transmission and reception on two different channels. Hand-off: The process of transferring the mobile station from one channel or base station to another. Page: A brief message that is broadcast over the entire service area by many base stations at the same time.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 24 / 303
  • 68. Control and traffic channelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 25 / 303
  • 69. Terminologies Half Duplex Systems: Two way communications are done using the same radio channel for both transmission and reception. At a given time the user can either transmit or receive.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 26 / 303
  • 70. Terminologies Half Duplex Systems: Two way communications are done using the same radio channel for both transmission and reception. At a given time the user can either transmit or receive. Mobile Switching Centre: Switching centre which coordinates the routing of calls in a large service area. In cellular radio system, the MSC connects the cellular base stations to the Public Switched Telephone Network (PSTN).Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 26 / 303
  • 71. Terminologies Half Duplex Systems: Two way communications are done using the same radio channel for both transmission and reception. At a given time the user can either transmit or receive. Mobile Switching Centre: Switching centre which coordinates the routing of calls in a large service area. In cellular radio system, the MSC connects the cellular base stations to the Public Switched Telephone Network (PSTN). Transceiver: A device capable of transmitting and receiving radio signals.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 26 / 303
  • 72. Full Duplex Systems Allow simultaneous transmission and reception between the subscriber and the base stationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 27 / 303
  • 73. Full Duplex Systems Allow simultaneous transmission and reception between the subscriber and the base station Full duplex is provided either by FDD or TDDCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 27 / 303
  • 74. Frequency Division Duplex (FDD) Both the base station and the subscriber unit transmit and receive signals simultaneously.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 28 / 303
  • 75. Frequency Division Duplex (FDD) Both the base station and the subscriber unit transmit and receive signals simultaneously. At the base station two separate transmit and receive antennas are used.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 28 / 303
  • 76. Frequency Division Duplex (FDD) Both the base station and the subscriber unit transmit and receive signals simultaneously. At the base station two separate transmit and receive antennas are used. At the subscriber unit only a single antenna is used both for transmission and reception. A device called a duplexer is used to enable the same antenna for transmission and reception simultaneously.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 28 / 303
  • 77. Time Division Duplex (TDD) Uses the fact that it is possible to share a single radio channel in time.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 29 / 303
  • 78. Time Division Duplex (TDD) Uses the fact that it is possible to share a single radio channel in time. A portion of time is used to transmit from the BS to the MS and the remaining time is used to transmit from the MS tot he BS.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 29 / 303
  • 79. Time Division Duplex (TDD) Uses the fact that it is possible to share a single radio channel in time. A portion of time is used to transmit from the BS to the MS and the remaining time is used to transmit from the MS tot he BS. Only possible with digital transmission formats and digital modulation (very sensitive to timing)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 29 / 303
  • 80. Time Division Duplex (TDD) Uses the fact that it is possible to share a single radio channel in time. A portion of time is used to transmit from the BS to the MS and the remaining time is used to transmit from the MS tot he BS. Only possible with digital transmission formats and digital modulation (very sensitive to timing) Used only for indoor or small area applications where the propagation delay are small.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 29 / 303
  • 81. The Cellular Concept:System Design Issues Cellular Systems - Basic Concepts(1) High capacity is achieved by limiting the coverage of each base station to a small geographic region called a cell.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 30 / 303
  • 82. The Cellular Concept:System Design Issues Cellular Systems - Basic Concepts(1) High capacity is achieved by limiting the coverage of each base station to a small geographic region called a cell. The same frequencies/time slots or codes are reused by spatially separating the base stations.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 30 / 303
  • 83. The Cellular Concept:System Design Issues Cellular Systems - Basic Concepts(1) High capacity is achieved by limiting the coverage of each base station to a small geographic region called a cell. The same frequencies/time slots or codes are reused by spatially separating the base stations. A switching technique called handoff enables a call to proceed uninterrupted when one user moves from one cell to another.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 30 / 303
  • 84. The Cellular Concept:System Design Issues Cellular Systems - Basic Concepts(1) High capacity is achieved by limiting the coverage of each base station to a small geographic region called a cell. The same frequencies/time slots or codes are reused by spatially separating the base stations. A switching technique called handoff enables a call to proceed uninterrupted when one user moves from one cell to another. Resolves the problem of limited radio spectrumCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 30 / 303
  • 85. The Cellular Concept:System Design Issues Cellular Systems - Basic Concepts(2) The neighbouring base stations are assigned different group of channels to minimize the interference.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 31 / 303
  • 86. The Cellular Concept:System Design Issues Cellular Systems - Basic Concepts(2) The neighbouring base stations are assigned different group of channels to minimize the interference. By systematically spacing base stations and the channel groups may be reused as many number off times as necessary.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 31 / 303
  • 87. The Cellular Concept:System Design Issues Cellular Systems - Basic Concepts(2) The neighbouring base stations are assigned different group of channels to minimize the interference. By systematically spacing base stations and the channel groups may be reused as many number off times as necessary. As demand increases the number of base stations get increased, there by providing additional capacity.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 31 / 303
  • 88. The Cellular Concept:System Design Issues Cellular Systems - Basic Concepts(3) Now let us understand how cellular networks is laid out. Figure: Bandwidth structureCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 32 / 303
  • 89. The Cellular Concept:System Design Issues Forward and Reverse channels: Forward Voice Channel: It is used for voice transmission from BS to MS.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 33 / 303
  • 90. The Cellular Concept:System Design Issues Forward and Reverse channels: Forward Voice Channel: It is used for voice transmission from BS to MS. Reverse Voice Channel: It is used for voice transmission from MS to BS.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 33 / 303
  • 91. The Cellular Concept:System Design Issues Forward and Reverse channels: Forward Voice Channel: It is used for voice transmission from BS to MS. Reverse Voice Channel: It is used for voice transmission from MS to BS. Forward Control Channel: Used for initiating a call from BS to MS.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 33 / 303
  • 92. The Cellular Concept:System Design Issues Forward and Reverse channels: Forward Voice Channel: It is used for voice transmission from BS to MS. Reverse Voice Channel: It is used for voice transmission from MS to BS. Forward Control Channel: Used for initiating a call from BS to MS. Reverse Control Channel: Used for initiating a call from MS to BS.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 33 / 303
  • 93. The Cellular Concept:System Design Issues Anatomy of a cellular call: A cell phone when turned on (not yet engaged in a call) scans the group of FCC to determine the one with the strongest signal. Please note that even if we are not making a call we use a battery power and that’s why when we buy a mobile phone we have two kinds of time available, one is the talk time and the other is the standby time.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 34 / 303
  • 94. The Cellular Concept:System Design Issues Anatomy of a cellular call: A cell phone when turned on (not yet engaged in a call) scans the group of FCC to determine the one with the strongest signal. Please note that even if we are not making a call we use a battery power and that’s why when we buy a mobile phone we have two kinds of time available, one is the talk time and the other is the standby time. The mobile phone monitors the channel and keeps on monitoring because if the strength drops below a certain threshold, it scans for the next strongest.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 34 / 303
  • 95. The Cellular Concept:System Design Issues Anatomy of a cellular call: A cell phone when turned on (not yet engaged in a call) scans the group of FCC to determine the one with the strongest signal. Please note that even if we are not making a call we use a battery power and that’s why when we buy a mobile phone we have two kinds of time available, one is the talk time and the other is the standby time. The mobile phone monitors the channel and keeps on monitoring because if the strength drops below a certain threshold, it scans for the next strongest. Control channels are defined and standardized over the entire area of service. Typically the control channels use up 5% of the total number of channels.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 34 / 303
  • 96. A call to a Mobile User:(1) The moment we dial the number the MSC which is connected to the PSTN dispatches the message to all the base stations. The BS and MSC is connected by means of a fibre, point-to-point microwave link. Once the message is broadcast to the base stations the base stations sends a paging message.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 35 / 303
  • 97. A call to a Mobile User:(1) The moment we dial the number the MSC which is connected to the PSTN dispatches the message to all the base stations. The BS and MSC is connected by means of a fibre, point-to-point microwave link. Once the message is broadcast to the base stations the base stations sends a paging message. The paging message contains the mobile identification number which the characteristic of that mobile station which is being broadcast. It is unique to that mobile. This number may not be same as the phone number. The MS receives the paging message from the BS it is monitoring.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 35 / 303
  • 98. A call to a Mobile User:(1) The moment we dial the number the MSC which is connected to the PSTN dispatches the message to all the base stations. The BS and MSC is connected by means of a fibre, point-to-point microwave link. Once the message is broadcast to the base stations the base stations sends a paging message. The paging message contains the mobile identification number which the characteristic of that mobile station which is being broadcast. It is unique to that mobile. This number may not be same as the phone number. The MS receives the paging message from the BS it is monitoring. It responds by identifying itself over the RCC. The BS coveys the handshake to the MSC. The MSC instructs the BS to move to an unused voice channel.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 35 / 303
  • 99. A call to a Mobile User:(2) The BS signals the MS to change over to an unused FVC and RVC.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 36 / 303
  • 100. A call to a Mobile User:(2) The BS signals the MS to change over to an unused FVC and RVC. A data message (called alert) is transmitted over the FVC to instruct the mobile to ring.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 36 / 303
  • 101. A call to a Mobile User:(2) The BS signals the MS to change over to an unused FVC and RVC. A data message (called alert) is transmitted over the FVC to instruct the mobile to ring. All of these sequences of events occur in just a few seconds, and a are not noticeable to the user.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 36 / 303
  • 102. A call to a Mobile User:(2) The BS signals the MS to change over to an unused FVC and RVC. A data message (called alert) is transmitted over the FVC to instruct the mobile to ring. All of these sequences of events occur in just a few seconds, and a are not noticeable to the user. While the call is in progress, the MSC adjusts the transmitted power in order to maintain the call quality.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 36 / 303
  • 103. A call from a Mobile User:(1) A call initiation request is sent to the RCC.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 37 / 303
  • 104. A call from a Mobile User:(1) A call initiation request is sent to the RCC. Along with this the MS transmits is MIN, Electronic serial number (ESN) and the phone number of the called party.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 37 / 303
  • 105. A call from a Mobile User:(1) A call initiation request is sent to the RCC. Along with this the MS transmits is MIN, Electronic serial number (ESN) and the phone number of the called party. The MS also transmits the station class mark (SCM) which indicates the maximum transmit power level for the particular user. This request is send toCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 37 / 303
  • 106. A call from a Mobile User:(1) A call initiation request is sent to the RCC. Along with this the MS transmits is MIN, Electronic serial number (ESN) and the phone number of the called party. The MS also transmits the station class mark (SCM) which indicates the maximum transmit power level for the particular user. This request is send to The base station which forwards the data to the mobile switching centre which validates the data and makes connection to the called party through the PSTN.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 37 / 303
  • 107. Frequency Reuse: Need(1) Suppose we have fixed telephone networks and they were running wires to every household.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 38 / 303
  • 108. Frequency Reuse: Need(1) Suppose we have fixed telephone networks and they were running wires to every household. Suppose we give every household their own allocation of radio spectrum for analog speech of 4 KHz bandwidth. Now we assume that there are 12.5 million households and for every 4 KHz allocation we need to have a 50 GHz of bandwidth.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 38 / 303
  • 109. Frequency Reuse: Need(1) Suppose we have fixed telephone networks and they were running wires to every household. Suppose we give every household their own allocation of radio spectrum for analog speech of 4 KHz bandwidth. Now we assume that there are 12.5 million households and for every 4 KHz allocation we need to have a 50 GHz of bandwidth. Clearly we cannot allow this kind of outage on a mobile phone network because we cannot reach that 50 GHz bandwidth and no other services possible using the radio transmissionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 38 / 303
  • 110. Frequency Reuse: Need(1) Suppose we have fixed telephone networks and they were running wires to every household. Suppose we give every household their own allocation of radio spectrum for analog speech of 4 KHz bandwidth. Now we assume that there are 12.5 million households and for every 4 KHz allocation we need to have a 50 GHz of bandwidth. Clearly we cannot allow this kind of outage on a mobile phone network because we cannot reach that 50 GHz bandwidth and no other services possible using the radio transmission Most of the spectrum unused most of the time. So frequency reuse is very necessary.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 38 / 303
  • 111. Frequency Reuse: Need(2) Cellular radio systems rely on intelligent allocation and reuse of channels throughout the coverage area.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 39 / 303
  • 112. Frequency Reuse: Need(2) Cellular radio systems rely on intelligent allocation and reuse of channels throughout the coverage area. Each BS is allocated a group of radio channels to be used within the small geographic area of its cell.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 39 / 303
  • 113. Frequency Reuse: Need(2) Cellular radio systems rely on intelligent allocation and reuse of channels throughout the coverage area. Each BS is allocated a group of radio channels to be used within the small geographic area of its cell. Neighbouring BS are given different channel allocation from each other.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 39 / 303
  • 114. Frequency Reuse: Need(2) Cellular radio systems rely on intelligent allocation and reuse of channels throughout the coverage area. Each BS is allocated a group of radio channels to be used within the small geographic area of its cell. Neighbouring BS are given different channel allocation from each other. By designing antennas and regulating the power, the coverage area within the cell is limited and the same group of frequencies are reused to cover another cell separated by a large enough distance to keep co-channel interference within limits. We wish to keep this co-channel interfering cell as far as possible because of the inverse square law that will take place.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 39 / 303
  • 115. Frequency Reuse: Need(3) On the other way if we put the co-channel interfering cells at a larger distance the less frequently we reuse the frequency, the less capacity we can have. So there is a trade-off between how much capacity we can pack in terms of closely putting the reuse factors and then we can go-ahead and reuse the frequency as and when desired.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 40 / 303
  • 116. Frequency Reuse: Need(3) On the other way if we put the co-channel interfering cells at a larger distance the less frequently we reuse the frequency, the less capacity we can have. So there is a trade-off between how much capacity we can pack in terms of closely putting the reuse factors and then we can go-ahead and reuse the frequency as and when desired. The design procedure for allocating channel groups for all the cellular BS within a system is called frequency reuse or frequency planning.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 40 / 303
  • 117. Frequency Reuse: Need(3) On the other way if we put the co-channel interfering cells at a larger distance the less frequently we reuse the frequency, the less capacity we can have. So there is a trade-off between how much capacity we can pack in terms of closely putting the reuse factors and then we can go-ahead and reuse the frequency as and when desired. The design procedure for allocating channel groups for all the cellular BS within a system is called frequency reuse or frequency planning. Frequency planning should not be very complicated because at the end we have to ensure that certain BS are using certain bands and others are using other bands and we cannot come up with a very complicated scheme.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 40 / 303
  • 118. Example of Frequency ReuseCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 41 / 303
  • 119. Cell Shape(1)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 42 / 303
  • 120. Cell Shape(2)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 43 / 303
  • 121. Cell Shape(3)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 44 / 303
  • 122. Cell Shape(4)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 45 / 303
  • 123. Cell Shape(5) Hexagonal cells are conceptualCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 46 / 303
  • 124. Cell Shape(5) Hexagonal cells are conceptual Theoretically hexagonal models are universally accepted because they have a shape that approximates a circle (for omni-directional radiation) and using hexagon geometry, fewest number of cells can cover the entire geographical region.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 46 / 303
  • 125. The Geometry of Hexagons(1)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 47 / 303
  • 126. The Geometry of Hexagons(2) The axes ”u” and ”v” intersect at 60 degrees as we already seen. To find the distance of a point P(u,v) from the origin Use x-y to to u-v coordinate transformation r2 = x2 + y2 x = u + vcos300 r = (v 2 + uv + u 2 )1/2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 48 / 303
  • 127. The Geometry of Hexagons(2) The axes ”u” and ”v” intersect at 60 degrees as we already seen. Unit cell is distance between cell centres. To find the distance of a point P(u,v) from the origin Use x-y to to u-v coordinate transformation r2 = x2 + y2 x = u + vcos300 r = (v 2 + uv + u 2 )1/2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 48 / 303
  • 128. The Geometry of Hexagons(2) The axes ”u” and ”v” intersect at 60 degrees as we already seen. Unit cell is distance between cell centres. If cell radius to point of a hexagon is R then 2R cos 300 = 1 or 1 R= √ 3 To find the distance of a point P(u,v) from the origin Use x-y to to u-v coordinate transformation r2 = x2 + y2 x = u + vcos300 r = (v 2 + uv + u 2 )1/2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 48 / 303
  • 129. The Geometry of Hexagons(3) Using this equation, to locate co-channel cells, we start from a reference cell and move i hexagons along the u axis then j hexagons along the v-axisCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 49 / 303
  • 130. The Geometry of Hexagons(3) Using this equation, to locate co-channel cells, we start from a reference cell and move i hexagons along the u axis then j hexagons along the v-axis Hence the distance between co-channel cells in adjacent clusters is given by D = (i 2 + ij + j 2 )1/2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 49 / 303
  • 131. The Geometry of Hexagons(3) Using this equation, to locate co-channel cells, we start from a reference cell and move i hexagons along the u axis then j hexagons along the v-axis Hence the distance between co-channel cells in adjacent clusters is given by D = (i 2 + ij + j 2 )1/2 The number of cells in a cluster N is given by N = i 2 + ij + j 2 , where i and j are integersCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 49 / 303
  • 132. The Geometry of Hexagons(3) Using this equation, to locate co-channel cells, we start from a reference cell and move i hexagons along the u axis then j hexagons along the v-axis Hence the distance between co-channel cells in adjacent clusters is given by D = (i 2 + ij + j 2 )1/2 The number of cells in a cluster N is given by N = i 2 + ij + j 2 , where i and j are integers Hence the possible values of N are 1,3,4,7,12.....Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 49 / 303
  • 133. ExampleCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 50 / 303
  • 134. In-ValidCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 51 / 303
  • 135. ValidCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 52 / 303
  • 136. Co-channel Cell Location(1) Method of locating co-channel cells Figure: Formation of a cluster for N=7 with i=2 and j=1Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 53 / 303
  • 137. Example Figure: Formation of a cluster for N=28 with i=2 and j=4Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 54 / 303
  • 138. ExampleCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 55 / 303
  • 139. Reuse Ratio(1)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 56 / 303
  • 140. Reuse Ratio(2) √ For hexagonal cells the reuse distance is given by D = 3NR, where R is the cell side and N is the cluster sizeCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 57 / 303
  • 141. Reuse Ratio(2) √ For hexagonal cells the reuse distance is given by D = 3NR, where R is the cell side and N is the cluster size D √ Reuse factor is q = = 3N RCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 57 / 303
  • 142. Cell Capacity and Reuse Consider a cellular system with s duplex channelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 58 / 303
  • 143. Cell Capacity and Reuse Consider a cellular system with s duplex channels Each cell is allocated k channels. Let these S channels be divided among N cells (cluster). Therefore S = KNCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 58 / 303
  • 144. Cell Capacity and Reuse Consider a cellular system with s duplex channels Each cell is allocated k channels. Let these S channels be divided among N cells (cluster). Therefore S = KN If a cluster of N cells is replicated M times in the system, total number of duplex channels C can be used as a measure of the system capacity C = MkN = MSCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 58 / 303
  • 145. Cell Capacity and Reuse Consider a cellular system with s duplex channels Each cell is allocated k channels. Let these S channels be divided among N cells (cluster). Therefore S = KN If a cluster of N cells is replicated M times in the system, total number of duplex channels C can be used as a measure of the system capacity C = MkN = MS If N is reduced, keeping cell size fixed, more clusters are required to cover the entire area. M ↑⇒ C ↑Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 58 / 303
  • 146. Cell Capacity and Reuse Consider a cellular system with s duplex channels Each cell is allocated k channels. Let these S channels be divided among N cells (cluster). Therefore S = KN If a cluster of N cells is replicated M times in the system, total number of duplex channels C can be used as a measure of the system capacity C = MkN = MS If N is reduced, keeping cell size fixed, more clusters are required to cover the entire area. M ↑⇒ C ↑ Smaller N ⇒ higher capacity ⇒ Larger co-channel interference ⇒ Lower QOSCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 58 / 303
  • 147. Cell Capacity and Reuse 1 Setup time: The time required to allocate a radio channel to a requesting user.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 59 / 303
  • 148. Cell Capacity and Reuse 1 Setup time: The time required to allocate a radio channel to a requesting user. 2 Blocked calls: A call that cannot be completed at the time of request due to congestion.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 59 / 303
  • 149. Cell Capacity and Reuse 1 Setup time: The time required to allocate a radio channel to a requesting user. 2 Blocked calls: A call that cannot be completed at the time of request due to congestion. 3 Holding Time: Average duration of a typical call.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 59 / 303
  • 150. Cell Capacity and Reuse 1 Setup time: The time required to allocate a radio channel to a requesting user. 2 Blocked calls: A call that cannot be completed at the time of request due to congestion. 3 Holding Time: Average duration of a typical call. 4 Request Rate: The average number of calls per unit time (λ)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 59 / 303
  • 151. Cell Capacity and Reuse 1 Setup time: The time required to allocate a radio channel to a requesting user. 2 Blocked calls: A call that cannot be completed at the time of request due to congestion. 3 Holding Time: Average duration of a typical call. 4 Request Rate: The average number of calls per unit time (λ) 5 Traffic Intensity: Measure of channel time utilization (Erlangs ⇒ A channel kept busy for one hour is defined as having a load of one Erlang)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 59 / 303
  • 152. Cell Capacity and Reuse 1 Setup time: The time required to allocate a radio channel to a requesting user. 2 Blocked calls: A call that cannot be completed at the time of request due to congestion. 3 Holding Time: Average duration of a typical call. 4 Request Rate: The average number of calls per unit time (λ) 5 Traffic Intensity: Measure of channel time utilization (Erlangs ⇒ A channel kept busy for one hour is defined as having a load of one Erlang) 6 Load: Traffic intensity across the entire radio system.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 59 / 303
  • 153. Cell Capacity and Reuse 1 Setup time: The time required to allocate a radio channel to a requesting user. 2 Blocked calls: A call that cannot be completed at the time of request due to congestion. 3 Holding Time: Average duration of a typical call. 4 Request Rate: The average number of calls per unit time (λ) 5 Traffic Intensity: Measure of channel time utilization (Erlangs ⇒ A channel kept busy for one hour is defined as having a load of one Erlang) 6 Load: Traffic intensity across the entire radio system. 7 Grade of Service: A measure of the congestion which is specified as a probability.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 59 / 303
  • 154. Traffic Theory The average number of MS requesting service (request/time) is called the average arrival rate (λ)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 60 / 303
  • 155. Traffic Theory The average number of MS requesting service (request/time) is called the average arrival rate (λ) The average time for the MS requires service is the average holding time (T)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 60 / 303
  • 156. Traffic Theory The average number of MS requesting service (request/time) is called the average arrival rate (λ) The average time for the MS requires service is the average holding time (T) The offered load is given by a = λ T (Erlangs)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 60 / 303
  • 157. Example Consider a cell with 100 MS and we assume that on an average 30 requests are generated during an hour (3600 sec) with average holding time t = 360 seconds (6 minutes)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 61 / 303
  • 158. Example Consider a cell with 100 MS and we assume that on an average 30 requests are generated during an hour (3600 sec) with average holding time t = 360 seconds (6 minutes) 30 Arrival rate λ = request/sec 3600Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 61 / 303
  • 159. Example Consider a cell with 100 MS and we assume that on an average 30 requests are generated during an hour (3600 sec) with average holding time t = 360 seconds (6 minutes) 30 Arrival rate λ = request/sec 3600 30 Offered load a = λt = × 360 = 3 Erlangs 3600Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 61 / 303
  • 160. Traffic Theory Average arrival rate during a short interval t is given by λ t (λt)n P(n, t) = × e −λt n! S(t) = 1 − e −µ tCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 62 / 303
  • 161. Traffic Theory Average arrival rate during a short interval t is given by λ t Assuming Poisson distribution of service requests the probability P(n,t) for n calls to arrive in an interval of length t is given by (λt)n P(n, t) = × e −λt n! S(t) = 1 − e −µ tCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 62 / 303
  • 162. Traffic Theory Average arrival rate during a short interval t is given by λ t Assuming Poisson distribution of service requests the probability P(n,t) for n calls to arrive in an interval of length t is given by (λt)n P(n, t) = × e −λt n! Assuming µ to be the service rate, probability of each call to terminate during interval t is given by µt. Thus probability of a given call requires service for time t or less is given by S(t) = 1 − e −µ tCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 62 / 303
  • 163. Erlang B and Erlang C Formulas Erlang B: Probability of an arriving call being blocked is given by Erlang B as 1 B(S, a) = . S S! ak k=0 k! S is the number of channels in the group as (s−a)!(s−a) C (S, a) = S−1 as ai (s−1)!(s−a) + i=0 i!Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 63 / 303
  • 164. Erlang B and Erlang C Formulas Erlang B: Probability of an arriving call being blocked is given by Erlang B as 1 B(S, a) = . S S! ak k=0 k! S is the number of channels in the group Erlang C: Probability of an arriving call being delayed is given by Erlang C as (s−a)!(s−a) C (S, a) = S−1 as ai (s−1)!(s−a) + i=0 i!Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 63 / 303
  • 165. Traffic Theory & Example Traffic nonblocked Efficiency = = Capacity Erlangs × Portions of non − routed traffic No. of trunks(channels) Example:Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 64 / 303
  • 166. Traffic Theory & Example Traffic nonblocked Efficiency = = Capacity Erlangs × Portions of non − routed traffic No. of trunks(channels) Example: Consider a cell with 2 channels and 100 MS which is generating 30 request/hour and the average holding time of each request is 360 seconds(6 min)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 64 / 303
  • 167. Traffic Theory & Example Traffic nonblocked Efficiency = = Capacity Erlangs × Portions of non − routed traffic No. of trunks(channels) Example: Consider a cell with 2 channels and 100 MS which is generating 30 request/hour and the average holding time of each request is 360 seconds(6 min) The total load offered is given by a = λt = 3 ErlangsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 64 / 303
  • 168. Traffic Theory & Example Traffic nonblocked Efficiency = = Capacity Erlangs × Portions of non − routed traffic No. of trunks(channels) Example: Consider a cell with 2 channels and 100 MS which is generating 30 request/hour and the average holding time of each request is 360 seconds(6 min) The total load offered is given by a = λt = 3 Erlangs By applying Erlang B formula the blocking probability B(s,a) = 0.53Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 64 / 303
  • 169. Traffic Theory & Example Traffic nonblocked Efficiency = = Capacity Erlangs × Portions of non − routed traffic No. of trunks(channels) Example: Consider a cell with 2 channels and 100 MS which is generating 30 request/hour and the average holding time of each request is 360 seconds(6 min) The total load offered is given by a = λt = 3 Erlangs By applying Erlang B formula the blocking probability B(s,a) = 0.53 Rerouted calls is 30 × 0.53 = 16 callsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 64 / 303
  • 170. Traffic Theory & Example Traffic nonblocked Efficiency = = Capacity Erlangs × Portions of non − routed traffic No. of trunks(channels) Example: Consider a cell with 2 channels and 100 MS which is generating 30 request/hour and the average holding time of each request is 360 seconds(6 min) The total load offered is given by a = λt = 3 Erlangs By applying Erlang B formula the blocking probability B(s,a) = 0.53 Rerouted calls is 30 × 0.53 = 16 calls 3 × (1 − 0.53) ∴ Efficiency = = 0.7 2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 64 / 303
  • 171. Erlang B chartCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 65 / 303
  • 172. Erlang C chartCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 66 / 303
  • 173. Example Consider a system with 100 cells and each cell having 20 channels which is generating 2 calls/hour and the average holding time of each request is 180 seconds(3 min). How many users will be supported if blocking probability is 2%Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 67 / 303
  • 174. Example Consider a system with 100 cells and each cell having 20 channels which is generating 2 calls/hour and the average holding time of each request is 180 seconds(3 min). How many users will be supported if blocking probability is 2% From Erlang B chart we get the total traffic is 13 ErlangsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 67 / 303
  • 175. Example Consider a system with 100 cells and each cell having 20 channels which is generating 2 calls/hour and the average holding time of each request is 180 seconds(3 min). How many users will be supported if blocking probability is 2% From Erlang B chart we get the total traffic is 13 Erlangs Traffic intensity per user = λt = 0.1 ErlangsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 67 / 303
  • 176. Example Consider a system with 100 cells and each cell having 20 channels which is generating 2 calls/hour and the average holding time of each request is 180 seconds(3 min). How many users will be supported if blocking probability is 2% From Erlang B chart we get the total traffic is 13 Erlangs Traffic intensity per user = λt = 0.1 Erlangs 13 Total no.of users that can be supported per cell = = 130 0.1 users/cellCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 67 / 303
  • 177. Example Consider a system with 100 cells and each cell having 20 channels which is generating 2 calls/hour and the average holding time of each request is 180 seconds(3 min). How many users will be supported if blocking probability is 2% From Erlang B chart we get the total traffic is 13 Erlangs Traffic intensity per user = λt = 0.1 Erlangs 13 Total no.of users that can be supported per cell = = 130 0.1 users/cell ∴ Total number of users that can be supported = 13,000Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 67 / 303
  • 178. Channel Assignment Strategies A scheme for increasing capacity and minimizing interference is requiredCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 68 / 303
  • 179. Channel Assignment Strategies A scheme for increasing capacity and minimizing interference is required They can be fixed or dynamic. Fixed assignment requires the advantage of planning and fixing whereas dynamic requires us to be adaptiveCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 68 / 303
  • 180. Channel Assignment Strategies A scheme for increasing capacity and minimizing interference is required They can be fixed or dynamic. Fixed assignment requires the advantage of planning and fixing whereas dynamic requires us to be adaptive Choice of channel assignment strategy impacts the performance of the system, particularly how a call is managed when a mobile user is handed off from one cell to anotherCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 68 / 303
  • 181. Channel Assignment Strategies A scheme for increasing capacity and minimizing interference is required They can be fixed or dynamic. Fixed assignment requires the advantage of planning and fixing whereas dynamic requires us to be adaptive Choice of channel assignment strategy impacts the performance of the system, particularly how a call is managed when a mobile user is handed off from one cell to another Capacity and hand-off are the two important requirementsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 68 / 303
  • 182. Fixed Channel Assignment Each cell is assigned a predetermined set of voice channelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 69 / 303
  • 183. Fixed Channel Assignment Each cell is assigned a predetermined set of voice channels Any call requests can be served only by the unused channels in that particular cellCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 69 / 303
  • 184. Fixed Channel Assignment Each cell is assigned a predetermined set of voice channels Any call requests can be served only by the unused channels in that particular cell If all the channels in the cell are occupied then the call is blockedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 69 / 303
  • 185. Fixed Channel Assignment Each cell is assigned a predetermined set of voice channels Any call requests can be served only by the unused channels in that particular cell If all the channels in the cell are occupied then the call is blocked In a variation of the fixed channel assignment, a cell can borrow channels from its neighbouring cell if its own channels are fullCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 69 / 303
  • 186. Dynamic Channel Assignment Voice channels are not allocated to different users permanentlyCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 70 / 303
  • 187. Dynamic Channel Assignment Voice channels are not allocated to different users permanently Each time a call request is made, the BS requests a channel from the MSCCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 70 / 303
  • 188. Dynamic Channel Assignment Voice channels are not allocated to different users permanently Each time a call request is made, the BS requests a channel from the MSC In a more complicated cellular system, there may be more than one MSCCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 70 / 303
  • 189. Dynamic Channel Assignment Voice channels are not allocated to different users permanently Each time a call request is made, the BS requests a channel from the MSC In a more complicated cellular system, there may be more than one MSC MSC allocates a channel to the requested cell using an algorithm which looks into the following parameters (i) The likelihood of future blocking (ii) The frequency of use of the channel (iii) The reuse distance of the channel (iv) Other cost functionsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 70 / 303
  • 190. Dynamic Channel Assignment Voice channels are not allocated to different users permanently Each time a call request is made, the BS requests a channel from the MSC In a more complicated cellular system, there may be more than one MSC MSC allocates a channel to the requested cell using an algorithm which looks into the following parameters (i) The likelihood of future blocking (ii) The frequency of use of the channel (iii) The reuse distance of the channel (iv) Other cost functions In the first level of design we are not looking into the variations of the channels. For example some channel may have high priorityCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 70 / 303
  • 191. Dynamic Channel Assignment To ensure minimum QOS, the MSC only allocates a given frequency if that frequency is not currently in use in the cell, or any other cell which falls within the limiting reuse distance.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 71 / 303
  • 192. Dynamic Channel Assignment To ensure minimum QOS, the MSC only allocates a given frequency if that frequency is not currently in use in the cell, or any other cell which falls within the limiting reuse distance. DCA reduces the likelihood of blocking, thus increasing the capacity of the systemCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 71 / 303
  • 193. Dynamic Channel Assignment To ensure minimum QOS, the MSC only allocates a given frequency if that frequency is not currently in use in the cell, or any other cell which falls within the limiting reuse distance. DCA reduces the likelihood of blocking, thus increasing the capacity of the system DCA strategy require the MSC to collect real time data on channel occupancy and traffic distribution on a continuous basisCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 71 / 303
  • 194. Handoff When a mobile moves into a different cell while the call is in progress, the MSC automatically transfers the call to a new channel belonging to the new BSCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 72 / 303
  • 195. Handoff When a mobile moves into a different cell while the call is in progress, the MSC automatically transfers the call to a new channel belonging to the new BS The handoff operation involves identifying a new BS and the allocation of voice and control signals associated with the new BS.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 72 / 303
  • 196. Handoff When a mobile moves into a different cell while the call is in progress, the MSC automatically transfers the call to a new channel belonging to the new BS The handoff operation involves identifying a new BS and the allocation of voice and control signals associated with the new BS. Handoffs must be performed successfully as infrequently as possible and must be imperceptible to the userCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 72 / 303
  • 197. Handoff When a mobile moves into a different cell while the call is in progress, the MSC automatically transfers the call to a new channel belonging to the new BS The handoff operation involves identifying a new BS and the allocation of voice and control signals associated with the new BS. Handoffs must be performed successfully as infrequently as possible and must be imperceptible to the user by looking at the variation of the signal strength from either BS, it is possible to decide on the optimum area where handoff can take place.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 72 / 303
  • 198. HandoffCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 73 / 303
  • 199. Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 74 / 303
  • 200. Handoff Hand-off is made when the received signal at the BS falls below a pre-specified thresholdCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 74 / 303
  • 201. Handoff Hand-off is made when the received signal at the BS falls below a pre-specified threshold In deciding when to hand-off, it is important to ensure that the drop in the signal level is not due to momentary fadingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 74 / 303
  • 202. Handoff Hand-off is made when the received signal at the BS falls below a pre-specified threshold In deciding when to hand-off, it is important to ensure that the drop in the signal level is not due to momentary fading Inorder to ensure this, the BS monitors the signal for a certain period of time before initiating hand-offCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 74 / 303
  • 203. Handoff Hand-off is made when the received signal at the BS falls below a pre-specified threshold In deciding when to hand-off, it is important to ensure that the drop in the signal level is not due to momentary fading Inorder to ensure this, the BS monitors the signal for a certain period of time before initiating hand-off The length of the time needed to decide if hand-off is necessary depends on the speed at which the MS is movingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 74 / 303
  • 204. Interference and system capacity Major limiting factor in the performance of cellular radio systemsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 75 / 303
  • 205. Interference and system capacity Major limiting factor in the performance of cellular radio systems It limits capacity and increases the number of dropped calls and has a direct correlation with the QOSCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 75 / 303
  • 206. Interference and system capacity Major limiting factor in the performance of cellular radio systems It limits capacity and increases the number of dropped calls and has a direct correlation with the QOS Sources of interference include (i) Another mobile in the same cell (ii) A call progressing in a neighbouring cell (iii) Other BS operating in the same frequency bandCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 75 / 303
  • 207. Interference and system capacity Major limiting factor in the performance of cellular radio systems It limits capacity and increases the number of dropped calls and has a direct correlation with the QOS Sources of interference include (i) Another mobile in the same cell (ii) A call progressing in a neighbouring cell (iii) Other BS operating in the same frequency band Very severe in urban areas due to greater RF noise and more number of MS and BSCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 75 / 303
  • 208. Interference and system capacity Major limiting factor in the performance of cellular radio systems It limits capacity and increases the number of dropped calls and has a direct correlation with the QOS Sources of interference include (i) Another mobile in the same cell (ii) A call progressing in a neighbouring cell (iii) Other BS operating in the same frequency band Very severe in urban areas due to greater RF noise and more number of MS and BS urban areas have an advantage, i.e the path loss exponent is high which leads to decreased interference levels.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 75 / 303
  • 209. Effects of Interference Voice Channels Cross talks Control channelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 76 / 303
  • 210. Effects of Interference Voice Channels Cross talks Noise in the background Control channelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 76 / 303
  • 211. Effects of Interference Voice Channels Cross talks Noise in the background Control channels Missed callsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 76 / 303
  • 212. Effects of Interference Voice Channels Cross talks Noise in the background Control channels Missed calls Blocked callsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 76 / 303
  • 213. Effects of Interference Voice Channels Cross talks Noise in the background Control channels Missed calls Blocked calls Dropped callsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 76 / 303
  • 214. Types of Interference Co-channel Interference: It is due to the cells that use the same set of frequenciesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 77 / 303
  • 215. Types of Interference Co-channel Interference: It is due to the cells that use the same set of frequencies Adjacent channel Interference: It is due to the signals that are adjacent in frequencyCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 77 / 303
  • 216. Co-channel InterferenceCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 78 / 303
  • 217. Co-channel Interference Unlike thermal noise CCI cannot be overcome by increasing the carrier power of the transmitterCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 79 / 303
  • 218. Co-channel Interference Unlike thermal noise CCI cannot be overcome by increasing the carrier power of the transmitter For similar sized cells the CCI is independent of the transmitted power and depends on the cell radius R and the distance to the nearest co-channel cell DCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 79 / 303
  • 219. Co-channel Interference Unlike thermal noise CCI cannot be overcome by increasing the carrier power of the transmitter For similar sized cells the CCI is independent of the transmitted power and depends on the cell radius R and the distance to the nearest co-channel cell D To reduce CCI the co-channel cells must be physically separatedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 79 / 303
  • 220. Co-channel Interference Unlike thermal noise CCI cannot be overcome by increasing the carrier power of the transmitter For similar sized cells the CCI is independent of the transmitted power and depends on the cell radius R and the distance to the nearest co-channel cell D To reduce CCI the co-channel cells must be physically separated D The co-channel reuse ratio Q = where D ⇒ distance between R co-channel BS and R ⇒ cell RadiusCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 79 / 303
  • 221. Co-channel Interference Unlike thermal noise CCI cannot be overcome by increasing the carrier power of the transmitter For similar sized cells the CCI is independent of the transmitted power and depends on the cell radius R and the distance to the nearest co-channel cell D To reduce CCI the co-channel cells must be physically separated D The co-channel reuse ratio Q = where D ⇒ distance between R co-channel BS and R ⇒ cell Radius It determines the spatial separation relative to the coverage distance of the cellCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 79 / 303
  • 222. Co-channel Interference Unlike thermal noise CCI cannot be overcome by increasing the carrier power of the transmitter For similar sized cells the CCI is independent of the transmitted power and depends on the cell radius R and the distance to the nearest co-channel cell D To reduce CCI the co-channel cells must be physically separated D The co-channel reuse ratio Q = where D ⇒ distance between R co-channel BS and R ⇒ cell Radius It determines the spatial separation relative to the coverage distance of the cell D √ For a hexagonal cell pattern, Q = = 3N RCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 79 / 303
  • 223. Co-channel Interference Unlike thermal noise CCI cannot be overcome by increasing the carrier power of the transmitter For similar sized cells the CCI is independent of the transmitted power and depends on the cell radius R and the distance to the nearest co-channel cell D To reduce CCI the co-channel cells must be physically separated D The co-channel reuse ratio Q = where D ⇒ distance between R co-channel BS and R ⇒ cell Radius It determines the spatial separation relative to the coverage distance of the cell D √ For a hexagonal cell pattern, Q = = 3N R Thus a smaller value of Q provides a larger capacity but higher CCI and hence there is a trade-off between capacity and interferenceCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 79 / 303
  • 224. Calculation of signal to interference ratio S/I The signal-to-interference ratio for a mobile is given by S S = m Where S is the desired signal strength and Ii is the I Ii i=1 interference caused by the i th co-channel cellCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 80 / 303
  • 225. Calculation of signal to interference ratio S/I The signal-to-interference ratio for a mobile is given by S S = m Where S is the desired signal strength and Ii is the I Ii i=1 interference caused by the i th co-channel cell The average received power at a distance d is given by −n d Pr = P0 d0Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 80 / 303
  • 226. Calculation of signal to interference ratio S/I The signal-to-interference ratio for a mobile is given by S S = m Where S is the desired signal strength and Ii is the I Ii i=1 interference caused by the i th co-channel cell The average received power at a distance d is given by −n d Pr = P0 d0 If Di is the distance of the i th interferer, the received power is proportional to (Di )−nCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 80 / 303
  • 227. Calculation of signal to interference ratio S/I The signal-to-interference ratio for a mobile is given by S S = m Where S is the desired signal strength and Ii is the I Ii i=1 interference caused by the i th co-channel cell The average received power at a distance d is given by −n d Pr = P0 d0 If Di is the distance of the i th interferer, the received power is proportional to (Di )−n The path loss exponent (n) ranges between 2 and 4Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 80 / 303
  • 228. Calculation of signal to interference ratio S/I S S R −n Thus the for a mobile can be written as = m I I (Di )−n i=1Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 81 / 303
  • 229. Calculation of signal to interference ratio S/I S S R −n Thus the for a mobile can be written as = m I I (Di )−n i=1 S (D/R)n For only the first layer of equidistant interferes = I mCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 81 / 303
  • 230. Calculation of signal to interference ratio S/I S S R −n Thus the for a mobile can be written as = m I I (Di )−n i=1 S (D/R)n For only the first layer of equidistant interferes = I m 1 √ n S 1 D n For a hexagonal cluster of cells = = 3N I 6 R 6Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 81 / 303
  • 231. Co-channel Interference S Hence is independent of the cell radius. ICellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 82 / 303
  • 232. Worst case of S/ICellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 83 / 303
  • 233. Worst case of S/I S (R)−n = I 2(D − R)−n + 2(D)−n + 2(D + R)−n Rearranging the equation we get S 1 = −n + 2(Q)−n + 2(Q + 1)−n I 2(Q − 1)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 84 / 303
  • 234. Adjacent Channel Interference This results from signals that are adjacent in frequency to the desired signals Near-Far Effect : When an interferer close to the BS radiates in the adjacent channel, while the subscriber is far away from the BS.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 85 / 303
  • 235. Adjacent Channel Interference This results from signals that are adjacent in frequency to the desired signals Results from imperfect receiver filters that allow nearby frequencies to leak in Near-Far Effect : When an interferer close to the BS radiates in the adjacent channel, while the subscriber is far away from the BS.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 85 / 303
  • 236. Adjacent Channel Interference This results from signals that are adjacent in frequency to the desired signals Results from imperfect receiver filters that allow nearby frequencies to leak in Problem can be severe if the interferer is very close to the subscriber’s receiver Near-Far Effect : When an interferer close to the BS radiates in the adjacent channel, while the subscriber is far away from the BS.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 85 / 303
  • 237. Adjacent Channel Interference ACI Can be reduced by (i) Careful filtering (ii) Careful Channel AssignmentCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 86 / 303
  • 238. Adjacent Channel Interference ACI Can be reduced by (i) Careful filtering (ii) Careful Channel Assignment The frequency separation between each channel in a cell should be made as large as possibleCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 86 / 303
  • 239. Adjacent Channel Interference ACI Can be reduced by (i) Careful filtering (ii) Careful Channel Assignment The frequency separation between each channel in a cell should be made as large as possible If the subscriber is at a distance d1 and the interferer is at d2 then signal to interference ratio (prior to filtering) is −n S d1 = I d2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 86 / 303
  • 240. Improving Capacity and Coverage Power control for interference reductionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 87 / 303
  • 241. Improving Capacity and Coverage Power control for interference reduction Cell splittingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 87 / 303
  • 242. Improving Capacity and Coverage Power control for interference reduction Cell splitting Cell sectoringCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 87 / 303
  • 243. Improving Capacity and Coverage Power control for interference reduction Cell splitting Cell sectoring Micro cell Zone ConceptCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 87 / 303
  • 244. Improving Capacity and Coverage Power control for interference reduction Cell splitting Cell sectoring Micro cell Zone Concept Use of RepeatersCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 87 / 303
  • 245. Power control for interference reduction In practical systems, the power level of every subscriber is under constant control by the serving BS.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 88 / 303
  • 246. Power control for interference reduction In practical systems, the power level of every subscriber is under constant control by the serving BS. Power control not only reduces interference levels but also prolongs battery lifeCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 88 / 303
  • 247. Power control for interference reduction In practical systems, the power level of every subscriber is under constant control by the serving BS. Power control not only reduces interference levels but also prolongs battery life IN CDMA power control is the key to ensure maximum utilization of the system capacity.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 88 / 303
  • 248. Power control for interference reduction In practical systems, the power level of every subscriber is under constant control by the serving BS. Power control not only reduces interference levels but also prolongs battery life IN CDMA power control is the key to ensure maximum utilization of the system capacity. Reduced interference leads to higher capacityCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 88 / 303
  • 249. Improving Capacity As demand increases, system designers have to provide more channels per unit coverage area.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 89 / 303
  • 250. Improving Capacity As demand increases, system designers have to provide more channels per unit coverage area. The common techniques for doing so are (i) Cell splitting (ii) Cell Sectoring (iii) Micro-cell ZoningCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 89 / 303
  • 251. Improving Capacity As demand increases, system designers have to provide more channels per unit coverage area. The common techniques for doing so are (i) Cell splitting (ii) Cell Sectoring (iii) Micro-cell Zoning Cell splitting increases the number of BS deployed and allows an ordely growth of the cellular systemCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 89 / 303
  • 252. Improving Capacity As demand increases, system designers have to provide more channels per unit coverage area. The common techniques for doing so are (i) Cell splitting (ii) Cell Sectoring (iii) Micro-cell Zoning Cell splitting increases the number of BS deployed and allows an ordely growth of the cellular system Sectoring uses directional antennas to further control the interference and frequency reuseCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 89 / 303
  • 253. Improving Capacity As demand increases, system designers have to provide more channels per unit coverage area. The common techniques for doing so are (i) Cell splitting (ii) Cell Sectoring (iii) Micro-cell Zoning Cell splitting increases the number of BS deployed and allows an ordely growth of the cellular system Sectoring uses directional antennas to further control the interference and frequency reuse Micro-cell zoning distributes the coverage of a cell and extends the cell boundary to hard-to-reach places.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 89 / 303
  • 254. Cell Splitting Cell splitting is the process of sub dividing a congested cell into smaller cells with (i) their own BS (ii) a corresponding reduction in the antenna height (iii) a corresponding reduction in the transmit powerCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 90 / 303
  • 255. Cell Splitting Cell splitting is the process of sub dividing a congested cell into smaller cells with (i) their own BS (ii) a corresponding reduction in the antenna height (iii) a corresponding reduction in the transmit power Splitting reduces the cell size and hence more number of cells to be usedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 90 / 303
  • 256. Cell Splitting Cell splitting is the process of sub dividing a congested cell into smaller cells with (i) their own BS (ii) a corresponding reduction in the antenna height (iii) a corresponding reduction in the transmit power Splitting reduces the cell size and hence more number of cells to be used More number of cells ⇒ more number of clusters ⇒ more channels ⇒ higher capacityCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 90 / 303
  • 257. Cell Splitting Cell splitting is the process of sub dividing a congested cell into smaller cells with (i) their own BS (ii) a corresponding reduction in the antenna height (iii) a corresponding reduction in the transmit power Splitting reduces the cell size and hence more number of cells to be used More number of cells ⇒ more number of clusters ⇒ more channels ⇒ higher capacity Cell splitting allows a system to grow by replacing large cells by small cells, without upsetting the channel allocationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 90 / 303
  • 258. Cell Splitting Cell splitting is the process of sub dividing a congested cell into smaller cells with (i) their own BS (ii) a corresponding reduction in the antenna height (iii) a corresponding reduction in the transmit power Splitting reduces the cell size and hence more number of cells to be used More number of cells ⇒ more number of clusters ⇒ more channels ⇒ higher capacity Cell splitting allows a system to grow by replacing large cells by small cells, without upsetting the channel allocation cells are split to add channels with no new spectrum usageCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 90 / 303
  • 259. Cell Splitting Cell splitting is the process of sub dividing a congested cell into smaller cells with (i) their own BS (ii) a corresponding reduction in the antenna height (iii) a corresponding reduction in the transmit power Splitting reduces the cell size and hence more number of cells to be used More number of cells ⇒ more number of clusters ⇒ more channels ⇒ higher capacity Cell splitting allows a system to grow by replacing large cells by small cells, without upsetting the channel allocation cells are split to add channels with no new spectrum usage Depending on the traffic patterns the smaller cells may be activated/deactivated inorder to efficiently use cell resourcesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 90 / 303
  • 260. Cell SplittingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 91 / 303
  • 261. Cell SplittingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 92 / 303
  • 262. Cell SplittingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 93 / 303
  • 263. Cell Splitting Suppose the cell radius of the new cells are reduced by half. What is the required transmit power for these new cells?Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 94 / 303
  • 264. Cell Splitting Suppose the cell radius of the new cells are reduced by half. What is the required transmit power for these new cells? We have Pr (old cell boundary) = Pt 1R −nCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 94 / 303
  • 265. Cell Splitting Suppose the cell radius of the new cells are reduced by half. What is the required transmit power for these new cells? We have Pr (old cell boundary) = Pt 1R −n R −n Pr (new cell boundary) = Pt 2 2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 94 / 303
  • 266. Cell Splitting Suppose the cell radius of the new cells are reduced by half. What is the required transmit power for these new cells? We have Pr (old cell boundary) = Pt 1R −n R −n Pr (new cell boundary) = Pt 2 2 Pt1 Pt2 = n which tells how much low power the new cell must 2 useCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 94 / 303
  • 267. Cell Splitting Suppose the cell radius of the new cells are reduced by half. What is the required transmit power for these new cells? We have Pr (old cell boundary) = Pt 1R −n R −n Pr (new cell boundary) = Pt 2 2 Pt1 Pt2 = n which tells how much low power the new cell must 2 use Pt1 For n=3 we get Pt2 = 8Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 94 / 303
  • 268. Cell Splitting Suppose the cell radius of the new cells are reduced by half. What is the required transmit power for these new cells? We have Pr (old cell boundary) = Pt 1R −n R −n Pr (new cell boundary) = Pt 2 2 Pt1 Pt2 = n which tells how much low power the new cell must 2 use Pt1 For n=3 we get Pt2 = 8 Thus the transmit power of new cells should be lower than than the original transmit powerCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 94 / 303
  • 269. Cell Splitting Assume that the congested cell service area is originally covered by single cells each cell with 50 channelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 95 / 303
  • 270. Cell Splitting Assume that the congested cell service area is originally covered by single cells each cell with 50 channels ∴ Original capacity = 1 × 50 = 50 for this cluster sizeCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 95 / 303
  • 271. Cell Splitting Assume that the congested cell service area is originally covered by single cells each cell with 50 channels ∴ Original capacity = 1 × 50 = 50 for this cluster size R After splitting Rnew = we have now 3 cells (smaller cells) 2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 95 / 303
  • 272. Cell Splitting Assume that the congested cell service area is originally covered by single cells each cell with 50 channels ∴ Original capacity = 1 × 50 = 50 for this cluster size R After splitting Rnew = we have now 3 cells (smaller cells) 2 New capacity = 3 × 50 = 150 users can be supportedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 95 / 303
  • 273. Cell Splitting Assume that the congested cell service area is originally covered by single cells each cell with 50 channels ∴ Original capacity = 1 × 50 = 50 for this cluster size R After splitting Rnew = we have now 3 cells (smaller cells) 2 New capacity = 3 × 50 = 150 users can be supported For different values of n , the transmit power will be calculated and it will be smaller for the new BSCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 95 / 303
  • 274. Cell Sectoring This is opposite to cell splitting where we do not make any D changes in R but we still try to reduce RCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 96 / 303
  • 275. Cell Sectoring This is opposite to cell splitting where we do not make any D changes in R but we still try to reduce R D ⇑ ⇓ interference and vice versa RCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 96 / 303
  • 276. Cell Sectoring This is opposite to cell splitting where we do not make any D changes in R but we still try to reduce R D ⇑ ⇓ interference and vice versa R Capacity is achieved by reducing the number of cells per cluster and thus increasing frequency reuseCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 96 / 303
  • 277. Cell Sectoring This is opposite to cell splitting where we do not make any D changes in R but we still try to reduce R D ⇑ ⇓ interference and vice versa R Capacity is achieved by reducing the number of cells per cluster and thus increasing frequency reuse The co-channel interference can be reduced by replacing omni-directional antennas by directional antennas radiating within a specified sectorCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 96 / 303
  • 278. Cell Sectoring This is opposite to cell splitting where we do not make any D changes in R but we still try to reduce R D ⇑ ⇓ interference and vice versa R Capacity is achieved by reducing the number of cells per cluster and thus increasing frequency reuse The co-channel interference can be reduced by replacing omni-directional antennas by directional antennas radiating within a specified sector A directional antenna transmits to and receives from only a fraction of the total number of co-channel cells. Thus CCI is reducedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 96 / 303
  • 279. Cell Sectoring This is opposite to cell splitting where we do not make any D changes in R but we still try to reduce R D ⇑ ⇓ interference and vice versa R Capacity is achieved by reducing the number of cells per cluster and thus increasing frequency reuse The co-channel interference can be reduced by replacing omni-directional antennas by directional antennas radiating within a specified sector A directional antenna transmits to and receives from only a fraction of the total number of co-channel cells. Thus CCI is reduced A cell is normally partitioned into 120 deg sectors , 90 deg sectors or 60 deg sectors. Moving from one sector to another sector requires a handoffCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 96 / 303
  • 280. Cell SectoringCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 97 / 303
  • 281. Cell SectoringCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 98 / 303
  • 282. Cell SectoringCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 99 / 303
  • 283. Problems with Cell Sectoring Increased no.of antennas at each BSCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 100 / 303
  • 284. Problems with Cell Sectoring Increased no.of antennas at each BS Decrease in trunking efficiency due to sectoringCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 100 / 303
  • 285. Problems with Cell Sectoring Increased no.of antennas at each BS Decrease in trunking efficiency due to sectoring Increased number of handoffsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 100 / 303
  • 286. Problems with Cell Sectoring Increased no.of antennas at each BS Decrease in trunking efficiency due to sectoring Increased number of handoffs Many modern BS support sectoring and related hand-offs without the help of MSCCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 100 / 303
  • 287. Microcell Zone Concept Different from both cell splitting and sectoringCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 101 / 303
  • 288. Microcell Zone Concept Different from both cell splitting and sectoring Problems in sectoring is solved using this conceptCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 101 / 303
  • 289. Microcell Zone Concept Different from both cell splitting and sectoring Problems in sectoring is solved using this concept A cell is divided into micro-cells or zonesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 101 / 303
  • 290. Microcell Zone Concept Different from both cell splitting and sectoring Problems in sectoring is solved using this concept A cell is divided into micro-cells or zones Each micro-cell or zone is connected to the same BSCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 101 / 303
  • 291. Microcell Zone Concept Different from both cell splitting and sectoring Problems in sectoring is solved using this concept A cell is divided into micro-cells or zones Each micro-cell or zone is connected to the same BS Each zone uses a directional antennaCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 101 / 303
  • 292. Microcell Zone Concept Different from both cell splitting and sectoring Problems in sectoring is solved using this concept A cell is divided into micro-cells or zones Each micro-cell or zone is connected to the same BS Each zone uses a directional antenna As mobile travels from one zone to another, no hand-ff is requiredCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 101 / 303
  • 293. Microcell Zone Concept Different from both cell splitting and sectoring Problems in sectoring is solved using this concept A cell is divided into micro-cells or zones Each micro-cell or zone is connected to the same BS Each zone uses a directional antenna As mobile travels from one zone to another, no hand-ff is required The BS simply switches the channel to the next zone siteCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 101 / 303
  • 294. Cell SectoringCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 102 / 303
  • 295. Microcell Zone Concept While the cell maintains a particular coverage area, the CCI is reduced becauseCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 103 / 303
  • 296. Microcell Zone Concept While the cell maintains a particular coverage area, the CCI is reduced because 1 Large central BS is replaced by several low power transmittersCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 103 / 303
  • 297. Microcell Zone Concept While the cell maintains a particular coverage area, the CCI is reduced because 1 Large central BS is replaced by several low power transmitters 2 Directional antennas are usedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 103 / 303
  • 298. Microcell Zone Concept While the cell maintains a particular coverage area, the CCI is reduced because 1 Large central BS is replaced by several low power transmitters 2 Directional antennas are used Decreased CCI improvesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 103 / 303
  • 299. Microcell Zone Concept While the cell maintains a particular coverage area, the CCI is reduced because 1 Large central BS is replaced by several low power transmitters 2 Directional antennas are used Decreased CCI improves 1 Signal qualityCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 103 / 303
  • 300. Microcell Zone Concept While the cell maintains a particular coverage area, the CCI is reduced because 1 Large central BS is replaced by several low power transmitters 2 Directional antennas are used Decreased CCI improves 1 Signal quality 2 CapacityCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 103 / 303
  • 301. Example S The desired is given by 18 dB and the path loss exponent is I n=4. How much capacity increase can occur if we use micro-zone cell concept by using 3 zones/cellCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 104 / 303
  • 302. Example S The desired is given by 18 dB and the path loss exponent is I n=4. How much capacity increase can occur if we use micro-zone cell concept by using 3 zones/cell S To achieve of 18 dB we need N=7 and we use 3 micro-cell I zone concept and create 3 zones within one cellCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 104 / 303
  • 303. Example S The desired is given by 18 dB and the path loss exponent is I n=4. How much capacity increase can occur if we use micro-zone cell concept by using 3 zones/cell S To achieve of 18 dB we need N=7 and we use 3 micro-cell I zone concept and create 3 zones within one cell This makes the cluster size to be N=3Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 104 / 303
  • 304. Example S The desired is given by 18 dB and the path loss exponent is I n=4. How much capacity increase can occur if we use micro-zone cell concept by using 3 zones/cell S To achieve of 18 dB we need N=7 and we use 3 micro-cell I zone concept and create 3 zones within one cell This makes the cluster size to be N=3 7 The capacity increase factor is = 2.33 3Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 104 / 303
  • 305. Repeaters for range Extension Useful for hard-to-reach areasCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 105 / 303
  • 306. Repeaters for range Extension Useful for hard-to-reach areas 1 Within buildings, basementsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 105 / 303
  • 307. Repeaters for range Extension Useful for hard-to-reach areas 1 Within buildings, basements 2 TunnelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 105 / 303
  • 308. Repeaters for range Extension Useful for hard-to-reach areas 1 Within buildings, basements 2 Tunnels 3 ValleysCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 105 / 303
  • 309. Repeaters for range Extension Useful for hard-to-reach areas 1 Within buildings, basements 2 Tunnels 3 Valleys Repeaters are bidirectionalCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 105 / 303
  • 310. Repeaters for range Extension Useful for hard-to-reach areas 1 Within buildings, basements 2 Tunnels 3 Valleys Repeaters are bidirectional 1 Receive signal from BSCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 105 / 303
  • 311. Repeaters for range Extension Useful for hard-to-reach areas 1 Within buildings, basements 2 Tunnels 3 Valleys Repeaters are bidirectional 1 Receive signal from BS 2 Amplify the signalsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 105 / 303
  • 312. Repeaters for range Extension Useful for hard-to-reach areas 1 Within buildings, basements 2 Tunnels 3 Valleys Repeaters are bidirectional 1 Receive signal from BS 2 Amplify the signals 3 Re-radiates the signalsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 105 / 303
  • 313. Unit 2 : Mobile Radio PropagationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 106 / 303
  • 314. Unit 2 : Mobile Radio Propagation 1 Basics of PropagationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 107 / 303
  • 315. Unit 2 : Mobile Radio Propagation 1 Basics of Propagation 2 Properties of Radio wavesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 107 / 303
  • 316. Unit 2 : Mobile Radio Propagation 1 Basics of Propagation 2 Properties of Radio waves 3 Radio Propagation MechanismsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 107 / 303
  • 317. Introduction 1 The mobile radio channel places a fundamental limitation on the performance of the wireless communication systemCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 108 / 303
  • 318. Introduction 1 The mobile radio channel places a fundamental limitation on the performance of the wireless communication system 2 The wireless transmission path may beCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 108 / 303
  • 319. Introduction 1 The mobile radio channel places a fundamental limitation on the performance of the wireless communication system 2 The wireless transmission path may be Line of sight (LOS)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 108 / 303
  • 320. Introduction 1 The mobile radio channel places a fundamental limitation on the performance of the wireless communication system 2 The wireless transmission path may be Line of sight (LOS) Non line of sight (NLOS)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 108 / 303
  • 321. Introduction 1 The mobile radio channel places a fundamental limitation on the performance of the wireless communication system 2 The wireless transmission path may be Line of sight (LOS) Non line of sight (NLOS) 3 Radio channels are often random and time varyingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 108 / 303
  • 322. Introduction 1 The mobile radio channel places a fundamental limitation on the performance of the wireless communication system 2 The wireless transmission path may be Line of sight (LOS) Non line of sight (NLOS) 3 Radio channels are often random and time varying 4 Modelling radio channels is one of the difficult task for the designersCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 108 / 303
  • 323. Introduction 1 The mobile radio channel places a fundamental limitation on the performance of the wireless communication system 2 The wireless transmission path may be Line of sight (LOS) Non line of sight (NLOS) 3 Radio channels are often random and time varying 4 Modelling radio channels is one of the difficult task for the designers 5 As most of the channels are random and time varying we go for deterministic channel modellingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 108 / 303
  • 324. Propagation Basics 1 Easy to generateCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 109 / 303
  • 325. Propagation Basics 1 Easy to generate 2 Can travel long distancesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 109 / 303
  • 326. Propagation Basics 1 Easy to generate 2 Can travel long distances 3 Can penetrate buildingsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 109 / 303
  • 327. Propagation Basics 1 Easy to generate 2 Can travel long distances 3 Can penetrate buildings 4 May be used for both indoor and outdoor communicationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 109 / 303
  • 328. Propagation Basics 1 Easy to generate 2 Can travel long distances 3 Can penetrate buildings 4 May be used for both indoor and outdoor communication 5 They are omni-directionalCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 109 / 303
  • 329. Propagation Basics 1 Easy to generate 2 Can travel long distances 3 Can penetrate buildings 4 May be used for both indoor and outdoor communication 5 They are omni-directional 6 Can be narrowly focused at high frequenciesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 109 / 303
  • 330. Propagation Basics 1 Frequency dependence ⇒ Behave morel like light at higher frequenciesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 110 / 303
  • 331. Propagation Basics 1 Frequency dependence ⇒ Behave morel like light at higher frequencies Difficulty in passing obstaclesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 110 / 303
  • 332. Propagation Basics 1 Frequency dependence ⇒ Behave morel like light at higher frequencies Difficulty in passing obstacles More direct pathsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 110 / 303
  • 333. Propagation Basics 1 Frequency dependence ⇒ Behave morel like light at higher frequencies Difficulty in passing obstacles More direct paths Absorbed by rainCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 110 / 303
  • 334. Propagation Basics 1 Frequency dependence ⇒ Behave morel like light at higher frequencies Difficulty in passing obstacles More direct paths Absorbed by rain 2 Frequency dependence ⇒ Behave morel like radio at lower frequenciesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 110 / 303
  • 335. Propagation Basics 1 Frequency dependence ⇒ Behave morel like light at higher frequencies Difficulty in passing obstacles More direct paths Absorbed by rain 2 Frequency dependence ⇒ Behave morel like radio at lower frequencies Can pass obstaclesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 110 / 303
  • 336. Propagation Basics 1 Frequency dependence ⇒ Behave morel like light at higher frequencies Difficulty in passing obstacles More direct paths Absorbed by rain 2 Frequency dependence ⇒ Behave morel like radio at lower frequencies Can pass obstacles Power falls off sharply with distance from sourceCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 110 / 303
  • 337. Propagation Basics 1 Frequency dependence ⇒ Behave morel like light at higher frequencies Difficulty in passing obstacles More direct paths Absorbed by rain 2 Frequency dependence ⇒ Behave morel like radio at lower frequencies Can pass obstacles Power falls off sharply with distance from source 3 Subject to interference from other radio wave sourcesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 110 / 303
  • 338. Propagation BasicsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 111 / 303
  • 339. Propagation BasicsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 112 / 303
  • 340. Propagation Basics Directional antennas are used Waves follow more direct paths LOS communication Reflected wave interferes with the original signalCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 113 / 303
  • 341. Propagation Basics 1 Modelling a radio channel is typically done in a statistical mannerCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 114 / 303
  • 342. Propagation Basics 1 Modelling a radio channel is typically done in a statistical manner 2 It is usually done based on measurement data specifically forCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 114 / 303
  • 343. Propagation Basics 1 Modelling a radio channel is typically done in a statistical manner 2 It is usually done based on measurement data specifically for The intended communication systemCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 114 / 303
  • 344. Propagation Basics 1 Modelling a radio channel is typically done in a statistical manner 2 It is usually done based on measurement data specifically for The intended communication system The intended spectrumCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 114 / 303
  • 345. Propagation Basics 1 Modelling a radio channel is typically done in a statistical manner 2 It is usually done based on measurement data specifically for The intended communication system The intended spectrum 3 For higher frequencies deterministic modelling is usedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 114 / 303
  • 346. Propagation Basics 1 Modelling a radio channel is typically done in a statistical manner 2 It is usually done based on measurement data specifically for The intended communication system The intended spectrum 3 For higher frequencies deterministic modelling is used 4 By making changes in the antenna height, coverage can be improvedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 114 / 303
  • 347. Propagation Basics 1 The free space received power is given by the Friis free space equation Pt Gt Gr λ2 Pr (d) = (1) (4π)2 d 2 LCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 115 / 303
  • 348. Propagation Basics 1 The free space received power is given by the Friis free space equation Pt Gt Gr λ2 Pr (d) = (1) (4π)2 d 2 L 2 The gain of an antenna is related to the effective aperture Ae by 4πAe Pr (d) = (2) λ2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 115 / 303
  • 349. Propagation Basics 1 The free space received power is given by the Friis free space equation Pt Gt Gr λ2 Pr (d) = (1) (4π)2 d 2 L 2 The gain of an antenna is related to the effective aperture Ae by 4πAe Pr (d) = (2) λ2 3 The effective aperture is related to the physical size of the antennaCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 115 / 303
  • 350. Propagation Basics 1 The free space received power is given by the Friis free space equation Pt Gt Gr λ2 Pr (d) = (1) (4π)2 d 2 L 2 The gain of an antenna is related to the effective aperture Ae by 4πAe Pr (d) = (2) λ2 3 The effective aperture is related to the physical size of the antenna 4 λ is related to the carrier frequencyCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 115 / 303
  • 351. Propagation Basics 1 The free space received power is given by the Friis free space equation Pt Gt Gr λ2 Pr (d) = (1) (4π)2 d 2 L 2 The gain of an antenna is related to the effective aperture Ae by 4πAe Pr (d) = (2) λ2 3 The effective aperture is related to the physical size of the antenna 4 λ is related to the carrier frequency 5 Higher the frequency, higher the gain for the same size antennaCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 115 / 303
  • 352. Definitions 1 An isotropic radiator is an ideal antenna that radiates power with unit gain uniformly in all directions. It is used as the reference antenna in wireless systemsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 116 / 303
  • 353. Definitions 1 An isotropic radiator is an ideal antenna that radiates power with unit gain uniformly in all directions. It is used as the reference antenna in wireless systems 2 Effective isotropic radiated power(EIRP) is defined as EIRP = Pt Gt (3)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 116 / 303
  • 354. Definitions 1 An isotropic radiator is an ideal antenna that radiates power with unit gain uniformly in all directions. It is used as the reference antenna in wireless systems 2 Effective isotropic radiated power(EIRP) is defined as EIRP = Pt Gt (3) 3 Effective radiated power is the power radiated in comparison to the half-wave dipole antennaCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 116 / 303
  • 355. Definitions 1 An isotropic radiator is an ideal antenna that radiates power with unit gain uniformly in all directions. It is used as the reference antenna in wireless systems 2 Effective isotropic radiated power(EIRP) is defined as EIRP = Pt Gt (3) 3 Effective radiated power is the power radiated in comparison to the half-wave dipole antenna 4 Since the dipole antenna has a gain of 1.64 ERP = EIRP = 2.15(dB)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 116 / 303
  • 356. Definitions 1 An isotropic radiator is an ideal antenna that radiates power with unit gain uniformly in all directions. It is used as the reference antenna in wireless systems 2 Effective isotropic radiated power(EIRP) is defined as EIRP = Pt Gt (3) 3 Effective radiated power is the power radiated in comparison to the half-wave dipole antenna 4 Since the dipole antenna has a gain of 1.64 ERP = EIRP = 2.15(dB) 5 In practice antenna gains are written in the units of dBI (dB gain with respect to an isotropic sourceCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 116 / 303
  • 357. Definitions 1 The Path loss represents the signal attenuation as a positive quantity and measured in dB Pt Gt Gr λ2 PL(dB) = 10 log = −10 log (4) Pr (4π)2 d 2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 117 / 303
  • 358. Definitions 1 The Path loss represents the signal attenuation as a positive quantity and measured in dB Pt Gt Gr λ2 PL(dB) = 10 log = −10 log (4) Pr (4π)2 d 2 2 When antenna gains are excluded we get Pt λ2 PL(dB) = 10 log = −10 log (5) Pr (4π)2 d 2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 117 / 303
  • 359. Propagation Basics 1 The Friis space model is valid in the far field or the Fraunhofer regionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 118 / 303
  • 360. Propagation Basics 1 The Friis space model is valid in the far field or the Fraunhofer region 2 The Fraunhofer distance is given by 2D 2 df = (6) λ where D is the largest physical linear dimension of the antennaCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 118 / 303
  • 361. Propagation Basics 1 The Friis space model is valid in the far field or the Fraunhofer region 2 The Fraunhofer distance is given by 2D 2 df = (6) λ where D is the largest physical linear dimension of the antenna 3 Additionally df must satisfy df ≥ D and df ≥ λCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 118 / 303
  • 362. Propagation Basics 1 The Friis space model is valid in the far field or the Fraunhofer region 2 The Fraunhofer distance is given by 2D 2 df = (6) λ where D is the largest physical linear dimension of the antenna 3 Additionally df must satisfy df ≥ D and df ≥ λ 4 The Friss space equation does not hold for d=0 and so for a close-in-distance we use d0 known as received power reference pointCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 118 / 303
  • 363. Propagation Basics 1 The Friis space model is valid in the far field or the Fraunhofer region 2 The Fraunhofer distance is given by 2D 2 df = (6) λ where D is the largest physical linear dimension of the antenna 3 Additionally df must satisfy df ≥ D and df ≥ λ 4 The Friss space equation does not hold for d=0 and so for a close-in-distance we use d0 known as received power reference point 5 The reference distance is chosen such that d0 > df . Thus 2 d0 Pr (d) = Pr (d0 ) log (7) dCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 118 / 303
  • 364. Propagation Basics 1 We often define the received power with reference to 1 mw as Pr (d0 ) d0 Pr (d) = 10 log + 20 log [indBm] (8) 0.001W dCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 119 / 303
  • 365. Propagation Basics 1 What will be the far field distance for a base station antenna with antenna dimension D = 0.5m and the frequency of operation f1 = 900/1800 MHz.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 120 / 303
  • 366. Propagation Basics 1 What will be the far field distance for a base station antenna with antenna dimension D = 0.5m and the frequency of operation f1 = 900/1800 MHz. 2 For 900 MHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 120 / 303
  • 367. Propagation Basics 1 What will be the far field distance for a base station antenna with antenna dimension D = 0.5m and the frequency of operation f1 = 900/1800 MHz. 2 For 900 MHz C We calculate λ = = 0.33m fCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 120 / 303
  • 368. Propagation Basics 1 What will be the far field distance for a base station antenna with antenna dimension D = 0.5m and the frequency of operation f1 = 900/1800 MHz. 2 For 900 MHz C We calculate λ = = 0.33m f 2D 2 We can use the formula df = = 1.5m λCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 120 / 303
  • 369. Propagation Basics 1 What will be the far field distance for a base station antenna with antenna dimension D = 0.5m and the frequency of operation f1 = 900/1800 MHz. 2 For 900 MHz C We calculate λ = = 0.33m f 2D 2 We can use the formula df = = 1.5m λ 3 For 1800 MHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 120 / 303
  • 370. Propagation Basics 1 What will be the far field distance for a base station antenna with antenna dimension D = 0.5m and the frequency of operation f1 = 900/1800 MHz. 2 For 900 MHz C We calculate λ = = 0.33m f 2D 2 We can use the formula df = = 1.5m λ 3 For 1800 MHz C We calculate λ = = 0.17m fCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 120 / 303
  • 371. Propagation Basics 1 What will be the far field distance for a base station antenna with antenna dimension D = 0.5m and the frequency of operation f1 = 900/1800 MHz. 2 For 900 MHz C We calculate λ = = 0.33m f 2D 2 We can use the formula df = = 1.5m λ 3 For 1800 MHz C We calculate λ = = 0.17m f 2D 2 We can use the formula df = = 3m λCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 120 / 303
  • 372. Propagation Basics The power flux density at a distance d from the radiating source is given by Pt Gt EIRP | E |2 Pd = = = W /m2 (9) 4πd 2 4πd 2 120πCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 121 / 303
  • 373. Radio Propagation MechanismsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 122 / 303
  • 374. Radio Propagation Mechanisms 1 Reflection occurs when the EM wave impinges on an object which has very large dimensions as compared to the wavelength. For example the surface of the Earth, buildings, walls etc.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 123 / 303
  • 375. Radio Propagation Mechanisms 1 Reflection occurs when the EM wave impinges on an object which has very large dimensions as compared to the wavelength. For example the surface of the Earth, buildings, walls etc. 2 Diffraction occurs when the radio path between the transmitter and receiver is obstructed by a surface that has sharp irregularities (edges)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 123 / 303
  • 376. Radio Propagation Mechanisms 1 Reflection occurs when the EM wave impinges on an object which has very large dimensions as compared to the wavelength. For example the surface of the Earth, buildings, walls etc. 2 Diffraction occurs when the radio path between the transmitter and receiver is obstructed by a surface that has sharp irregularities (edges) 3 Scattering occurs when the medium has objects that are smaller or comparable to the wavelengthCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 123 / 303
  • 377. Radio Propagation Mechanisms - Reflection 1 It occurs when a radio wave in one medium impinges upon another medium having different electrical propertiesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 124 / 303
  • 378. Radio Propagation Mechanisms - Reflection 1 It occurs when a radio wave in one medium impinges upon another medium having different electrical properties 2 If the radio wave is incident on a perfect dielectricCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 124 / 303
  • 379. Radio Propagation Mechanisms - Reflection 1 It occurs when a radio wave in one medium impinges upon another medium having different electrical properties 2 If the radio wave is incident on a perfect dielectric Part of the energy is reflected backCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 124 / 303
  • 380. Radio Propagation Mechanisms - Reflection 1 It occurs when a radio wave in one medium impinges upon another medium having different electrical properties 2 If the radio wave is incident on a perfect dielectric Part of the energy is reflected back Part of the energy is transmittedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 124 / 303
  • 381. Radio Propagation Mechanisms - Reflection 1 It occurs when a radio wave in one medium impinges upon another medium having different electrical properties 2 If the radio wave is incident on a perfect dielectric Part of the energy is reflected back Part of the energy is transmitted 3 The electric field intensity of the reflected and transmitted waves can be related by the Fresnel coefficient ΓCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 124 / 303
  • 382. Radio Propagation Mechanisms - Reflection 1 It occurs when a radio wave in one medium impinges upon another medium having different electrical properties 2 If the radio wave is incident on a perfect dielectric Part of the energy is reflected back Part of the energy is transmitted 3 The electric field intensity of the reflected and transmitted waves can be related by the Fresnel coefficient Γ 4 If incident on a perfect conductor, the entire energy is reflected backCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 124 / 303
  • 383. Radio Propagation Mechanisms 1 In general the EM waves are polarizedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 125 / 303
  • 384. Radio Propagation Mechanisms 1 In general the EM waves are polarized They have instantaneous electric field components in orthogonal directions in spaceCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 125 / 303
  • 385. Radio Propagation Mechanisms 1 In general the EM waves are polarized They have instantaneous electric field components in orthogonal directions in space 2 A polarized wave can be represented as a sum of two spatially orthogonal componentsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 125 / 303
  • 386. Radio Propagation Mechanisms 1 In general the EM waves are polarized They have instantaneous electric field components in orthogonal directions in space 2 A polarized wave can be represented as a sum of two spatially orthogonal components Vertical or HorizontalCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 125 / 303
  • 387. Radio Propagation Mechanisms 1 In general the EM waves are polarized They have instantaneous electric field components in orthogonal directions in space 2 A polarized wave can be represented as a sum of two spatially orthogonal components Vertical or Horizontal Left hand or Right hand circularly polarizedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 125 / 303
  • 388. Radio Propagation Mechanisms 1 In general the EM waves are polarized They have instantaneous electric field components in orthogonal directions in space 2 A polarized wave can be represented as a sum of two spatially orthogonal components Vertical or Horizontal Left hand or Right hand circularly polarized 3 Polarization can also be used as a degree of freedom for frequency planningCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 125 / 303
  • 389. Reflection from dielectricsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 126 / 303
  • 390. Reflection from dielectrics 1 The reflection coefficient (Fresnels) is given by Er η2 sin θt − η1 sin θi Γ|| = = (10) Ei η2 sin θt + η1 sin θi Er η2 sin θi − η1 sin θt Γ⊥ = = (11) Ei η2 sin θi + η1 sin θtCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 127 / 303
  • 391. Reflection from dielectrics 1 The reflection coefficient (Fresnels) is given by Er η2 sin θt − η1 sin θi Γ|| = = (10) Ei η2 sin θt + η1 sin θi Er η2 sin θi − η1 sin θt Γ⊥ = = (11) Ei η2 sin θi + η1 sin θt 2 ηi is the intrinsic impedance which is given by µi ηi = (12) i µi ⇒ Permeability of the dielectric i ⇒ Permittivity of the dielectricCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 127 / 303
  • 392. Reflection from Perfect Conductors 1 Electromagnetic energy cannot pass through perfect conductorsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 128 / 303
  • 393. Reflection from Perfect Conductors 1 Electromagnetic energy cannot pass through perfect conductors 2 All the energy is reflected backCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 128 / 303
  • 394. Reflection from Perfect Conductors 1 Electromagnetic energy cannot pass through perfect conductors 2 All the energy is reflected back 3 Thus we haveCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 128 / 303
  • 395. Reflection from Perfect Conductors 1 Electromagnetic energy cannot pass through perfect conductors 2 All the energy is reflected back 3 Thus we have θi = θrCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 128 / 303
  • 396. Reflection from Perfect Conductors 1 Electromagnetic energy cannot pass through perfect conductors 2 All the energy is reflected back 3 Thus we have θi = θr Ei = Er (Electric field in the plane of incidence)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 128 / 303
  • 397. Reflection from Perfect Conductors 1 Electromagnetic energy cannot pass through perfect conductors 2 All the energy is reflected back 3 Thus we have θi = θr Ei = Er (Electric field in the plane of incidence) Ei = −Er (Electric field normal to the plane of incidence)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 128 / 303
  • 398. Reflection from Perfect Conductors 1 Electromagnetic energy cannot pass through perfect conductors 2 All the energy is reflected back 3 Thus we have θi = θr Ei = Er (Electric field in the plane of incidence) Ei = −Er (Electric field normal to the plane of incidence) Γ|| = 1 and Γ⊥ = −1Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 128 / 303
  • 399. Ground Reflection Models 1 This is important in LOS pathCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 129 / 303
  • 400. Ground Reflection Models 1 This is important in LOS path 2 A two-ray ground reflection model is often usedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 129 / 303
  • 401. Ground Reflection Models 1 This is important in LOS path 2 A two-ray ground reflection model is often used 3 This model is reasonably accurate for predicting large scale signal strength over several kilometresCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 129 / 303
  • 402. Ground Reflection Models 1 This is important in LOS path 2 A two-ray ground reflection model is often used 3 This model is reasonably accurate for predicting large scale signal strength over several kilometres 4 Here we assume that the height of the transmitter is greater than 50 mCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 129 / 303
  • 403. Two Ray Ground Reflection ModelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 130 / 303
  • 404. Two Ray Ground Reflection ModelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 131 / 303
  • 405. Ground Reflection Models 2ht hr ∆ = d || − d | = (ht + hr )2 + d 2 − (ht − hr )2 + d 2 = (13) d 2π∆ ∆ωc Phase difference θ∆ = = (14) λ c ∆ θ∆ Time Delay Td = = (15) c 2πfc 2 hr ht Pr = Pt Gt Gr (16) d2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 132 / 303
  • 406. Diffraction 1 It occurs when the radio path between the transmitter and receiver is obstructed by a surface that has sharp edgesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 133 / 303
  • 407. Diffraction 1 It occurs when the radio path between the transmitter and receiver is obstructed by a surface that has sharp edges 2 It explains how radio signals can travel urban and rural environments without a line of sight path.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 133 / 303
  • 408. Diffraction 1 It occurs when the radio path between the transmitter and receiver is obstructed by a surface that has sharp edges 2 It explains how radio signals can travel urban and rural environments without a line of sight path. 3 Diffraction can be explained by huygens principleCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 133 / 303
  • 409. Diffraction 1 It occurs when the radio path between the transmitter and receiver is obstructed by a surface that has sharp edges 2 It explains how radio signals can travel urban and rural environments without a line of sight path. 3 Diffraction can be explained by huygens principle All points on a wave-front can be considered as point sources for the production of secondary waveletsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 133 / 303
  • 410. Knife-edge Diffraction ModelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 134 / 303
  • 411. Diffraction Gain 2(d1 + d2 ) ν=h (17) λd1 d2 The diffraction gain due to knife edge is given by Gd (dB) = 0 ν ≤ −1 Gd (dB) = 20 log(0.5 − 0.62 ν) −1≤ν ≤0 Gd (dB) = 20 log(0.5exp(−0.950)) 0≤ν≤1 Gd (dB) = 20 log(0.4 − 0.1184 − (0.38 − 0.10)2 ) 1 ≤ ν ≤ 2.4 0.225 Gd (dB) = 20 log ν > 2.4 νCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 135 / 303
  • 412. Multiple knife-edge DiffractionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 136 / 303
  • 413. Scattering 1 occurs when the medium has objects that are smaller or comparable to the wavelengthCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 137 / 303
  • 414. Scattering 1 occurs when the medium has objects that are smaller or comparable to the wavelength 2 Follows the same principles with diffractionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 137 / 303
  • 415. Scattering 1 occurs when the medium has objects that are smaller or comparable to the wavelength 2 Follows the same principles with diffraction 3 Causes the transmitter energy to be radiated in many directions eg: foliage, street signs, lamp partsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 137 / 303
  • 416. Multiple knife-edge DiffractionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 138 / 303
  • 417. Multiple knife-edge DiffractionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 139 / 303
  • 418. Mobile Radio Propagation 1 Free Space Propagation modelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 140 / 303
  • 419. Mobile Radio Propagation 1 Free Space Propagation model 2 Small scale propagation modelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 140 / 303
  • 420. Mobile Radio Propagation 1 Free Space Propagation model 2 Small scale propagation model 3 Large scale propagation modelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 140 / 303
  • 421. Mobile Radio Propagation 1 Free Space Propagation model 2 Small scale propagation model 3 Large scale propagation model 4 Log-Distance path loss modelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 140 / 303
  • 422. Mobile Radio Propagation 1 Free Space Propagation model 2 Small scale propagation model 3 Large scale propagation model 4 Log-Distance path loss model 5 Log-Normal shadowingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 140 / 303
  • 423. Need for Propagation Models 1 Determining the coverage area of the transmitterCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 141 / 303
  • 424. Need for Propagation Models 1 Determining the coverage area of the transmitter Determine the transmitter power requirementCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 141 / 303
  • 425. Need for Propagation Models 1 Determining the coverage area of the transmitter Determine the transmitter power requirement Determine the battery life timeCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 141 / 303
  • 426. Need for Propagation Models 1 Determining the coverage area of the transmitter Determine the transmitter power requirement Determine the battery life time 2 Finding modulation and coding schemes to improve the channel qualityCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 141 / 303
  • 427. Need for Propagation Models 1 Determining the coverage area of the transmitter Determine the transmitter power requirement Determine the battery life time 2 Finding modulation and coding schemes to improve the channel quality Determine the maximum channel capacityCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 141 / 303
  • 428. Free space Propagation Model 1 Used to predict the received signal strength in case of a clear LOS path between transmitter and receiver eg: satellite communication Pt Gt Gr λ2 Pr (d) = (18) (4π)2 d 2 LCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 142 / 303
  • 429. Free space Propagation Model 1 Here we take the system loss factor into considerationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 143 / 303
  • 430. Free space Propagation Model 1 Here we take the system loss factor into consideration 2 Received power falls off as the square of the distance at the rate of 20 dB/decadeCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 143 / 303
  • 431. Free space Propagation Model 1 Here we take the system loss factor into consideration 2 Received power falls off as the square of the distance at the rate of 20 dB/decade 3 L = LP LS LFCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 143 / 303
  • 432. Free space Propagation Model 1 Here we take the system loss factor into consideration 2 Received power falls off as the square of the distance at the rate of 20 dB/decade 3 L = LP LS LF 4 For Friis equation to hold, distance d should be in the far field of the transmitting antennaCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 143 / 303
  • 433. Free space Propagation Model 1 Here we take the system loss factor into consideration 2 Received power falls off as the square of the distance at the rate of 20 dB/decade 3 L = LP LS LF 4 For Friis equation to hold, distance d should be in the far field of the transmitting antenna 5 The far field is defined as given by the following equation 2D 2 df = (19) λ Where D is the largest physical dimension of the antennaCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 143 / 303
  • 434. Free space Propagation Model 1 Here we take the system loss factor into consideration 2 Received power falls off as the square of the distance at the rate of 20 dB/decade 3 L = LP LS LF 4 For Friis equation to hold, distance d should be in the far field of the transmitting antenna 5 The far field is defined as given by the following equation 2D 2 df = (19) λ Where D is the largest physical dimension of the antenna 6 Friis equation does not hold for d = 0Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 143 / 303
  • 435. Free space Propagation Model 1 Here we take the system loss factor into consideration 2 Received power falls off as the square of the distance at the rate of 20 dB/decade 3 L = LP LS LF 4 For Friis equation to hold, distance d should be in the far field of the transmitting antenna 5 The far field is defined as given by the following equation 2D 2 df = (19) λ Where D is the largest physical dimension of the antenna 6 Friis equation does not hold for d = 0 7 So for close distances we use a reference distance d0 which should be ≥ dfCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 143 / 303
  • 436. Free space Propagation Model 1 Power received at a distance d > d0 is given by 2 d0 Pr (d) = Pr (d0 ) d > d0 > df (20) d Where d0 is the reference distance, df is the Fraunhofer distanceCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 144 / 303
  • 437. Free space Propagation Model 1 Power received at a distance d > d0 is given by 2 d0 Pr (d) = Pr (d0 ) d > d0 > df (20) d Where d0 is the reference distance, df is the Fraunhofer distance 2 Power level in dBm is defined as Pr (d0 )W d0 Pr (d) = 10 log + 20 log (dBm) d > d0 > df 0.001W d (21)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 144 / 303
  • 438. Free space Propagation Model 1 Power received at a distance d > d0 is given by 2 d0 Pr (d) = Pr (d0 ) d > d0 > df (20) d Where d0 is the reference distance, df is the Fraunhofer distance 2 Power level in dBm is defined as Pr (d0 )W d0 Pr (d) = 10 log + 20 log (dBm) d > d0 > df 0.001W d (21) 3 Path loss refers to the signal attenuation and is the difference between the effective transmit power and receive power Pt Gt Gr λ2 PL (dB) = −10 log = −10 log (22) Pr (4π)2 d 2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 144 / 303
  • 439. Free space Propagation Model 1 If we make Gt and Gr as one (unit gain) PL (dB) = 32.45 + 20 log10 fc (MHz) + 20 log10 d (km) (23)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 145 / 303
  • 440. Free space Propagation Model 1 If we make Gt and Gr as one (unit gain) PL (dB) = 32.45 + 20 log10 fc (MHz) + 20 log10 d (km) (23) 2 This equation is used for predicting the path lossCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 145 / 303
  • 441. Free space Propagation Model 1 If we make Gt and Gr as one (unit gain) PL (dB) = 32.45 + 20 log10 fc (MHz) + 20 log10 d (km) (23) 2 This equation is used for predicting the path loss 3 Higher frequency means higher lossesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 145 / 303
  • 442. Radio Propagation Models 1 It needs to characterize the signal strength received after undergoing reflections, diffraction and scatteringCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 146 / 303
  • 443. Radio Propagation Models 1 It needs to characterize the signal strength received after undergoing reflections, diffraction and scattering Small-Scale Propagation ModelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 146 / 303
  • 444. Radio Propagation Models 1 It needs to characterize the signal strength received after undergoing reflections, diffraction and scattering Small-Scale Propagation Models Large-Scale Propagation ModelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 146 / 303
  • 445. Radio Propagation Models 1 It needs to characterize the signal strength received after undergoing reflections, diffraction and scattering Small-Scale Propagation Models Large-Scale Propagation Models 2 Radio Propagation models can be calculated byCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 146 / 303
  • 446. Radio Propagation Models 1 It needs to characterize the signal strength received after undergoing reflections, diffraction and scattering Small-Scale Propagation Models Large-Scale Propagation Models 2 Radio Propagation models can be calculated by Using empherical methodsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 146 / 303
  • 447. Radio Propagation Models 1 It needs to characterize the signal strength received after undergoing reflections, diffraction and scattering Small-Scale Propagation Models Large-Scale Propagation Models 2 Radio Propagation models can be calculated by Using empherical methods Using analytical methodsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 146 / 303
  • 448. Small Scale Propagation Models 1 As the user moves over small distances the instantaneous received signal will fluctuate rapidly giving rise to small scale fadingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 147 / 303
  • 449. Small Scale Propagation Models 1 As the user moves over small distances the instantaneous received signal will fluctuate rapidly giving rise to small scale fading 2 The reason for that is the signal coming from many directionsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 147 / 303
  • 450. Small Scale Propagation Models 1 As the user moves over small distances the instantaneous received signal will fluctuate rapidly giving rise to small scale fading 2 The reason for that is the signal coming from many directions 3 When we try to interpret the signals at the receiver the sum behaves like a noise (Rayleigh fading) since the phases of the signals are randomCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 147 / 303
  • 451. Small Scale Propagation Models 1 As the user moves over small distances the instantaneous received signal will fluctuate rapidly giving rise to small scale fading 2 The reason for that is the signal coming from many directions 3 When we try to interpret the signals at the receiver the sum behaves like a noise (Rayleigh fading) since the phases of the signals are random 4 In small scale fading the received signal power may change as much as 3 or 4 orders of magnitude when the receiver is only moved a fraction of the wavelengthCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 147 / 303
  • 452. Small Scale Propagation Models 1 As the user moves over small distances the instantaneous received signal will fluctuate rapidly giving rise to small scale fading 2 The reason for that is the signal coming from many directions 3 When we try to interpret the signals at the receiver the sum behaves like a noise (Rayleigh fading) since the phases of the signals are random 4 In small scale fading the received signal power may change as much as 3 or 4 orders of magnitude when the receiver is only moved a fraction of the wavelength 5 Small T-R separation distancesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 147 / 303
  • 453. Small Scale Propagation Models 1 As the user moves over small distances the instantaneous received signal will fluctuate rapidly giving rise to small scale fading 2 The reason for that is the signal coming from many directions 3 When we try to interpret the signals at the receiver the sum behaves like a noise (Rayleigh fading) since the phases of the signals are random 4 In small scale fading the received signal power may change as much as 3 or 4 orders of magnitude when the receiver is only moved a fraction of the wavelength 5 Small T-R separation distances 6 Heavily populated areasCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 147 / 303
  • 454. Small Scale Propagation Models 1 Main propagation model is scatteringCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 148 / 303
  • 455. Small Scale Propagation Models 1 Main propagation model is scattering 2 Multiple waves reach at the receiver at different times and finding the vector sum results in fadingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 148 / 303
  • 456. Small Scale Propagation Models 1 Main propagation model is scattering 2 Multiple waves reach at the receiver at different times and finding the vector sum results in fading 3 Distribution of signal attenuation coefficient : Rayleigh (LOS) , Rician (NLOS)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 148 / 303
  • 457. Small Scale Propagation Models 1 Main propagation model is scattering 2 Multiple waves reach at the receiver at different times and finding the vector sum results in fading 3 Distribution of signal attenuation coefficient : Rayleigh (LOS) , Rician (NLOS) 4 Short term fading modelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 148 / 303
  • 458. Small Scale Propagation Models 1 Main propagation model is scattering 2 Multiple waves reach at the receiver at different times and finding the vector sum results in fading 3 Distribution of signal attenuation coefficient : Rayleigh (LOS) , Rician (NLOS) 4 Short term fading model 5 Rapid and severe signal fluctuations around a slowly varying meanCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 148 / 303
  • 459. Large Scale Propagation Models 1 The model that predict the mean signal strength for an arbitrary T-R separation distance are called large scale propagation modelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 149 / 303
  • 460. Large Scale Propagation Models 1 The model that predict the mean signal strength for an arbitrary T-R separation distance are called large scale propagation models 2 As the mobile moves away from the transmitter over large distances the local average received signal will gradually decreaseCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 149 / 303
  • 461. Large Scale Propagation Models 1 The model that predict the mean signal strength for an arbitrary T-R separation distance are called large scale propagation models 2 As the mobile moves away from the transmitter over large distances the local average received signal will gradually decrease 3 This is called large scale path loss and is calculated by averaging signal measurementsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 149 / 303
  • 462. Large Scale Propagation Models 1 The model that predict the mean signal strength for an arbitrary T-R separation distance are called large scale propagation models 2 As the mobile moves away from the transmitter over large distances the local average received signal will gradually decrease 3 This is called large scale path loss and is calculated by averaging signal measurements 4 Main propagation mechanism is reflectionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 149 / 303
  • 463. Small and Large Scale Propagation ModelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 150 / 303
  • 464. Small and Large Scale Propagation ModelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 151 / 303
  • 465. Small and Large Scale Propagation ModelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 152 / 303
  • 466. Large and Small Scale Propagation Models 1 Long distance path loss modelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 153 / 303
  • 467. Large and Small Scale Propagation Models 1 Long distance path loss model Both theoretical and measurement based models show that received signal power decreases logarithmically with distancesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 153 / 303
  • 468. Large and Small Scale Propagation Models 1 Long distance path loss model Both theoretical and measurement based models show that received signal power decreases logarithmically with distances Both for indoor and outdoor channelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 153 / 303
  • 469. Small and Large Scale Propagation ModelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 154 / 303
  • 470. Log-Distance Path Loss Models 1 The average large scale path loss for an arbitrary T-R separation is expressed as a function of distance using a path loss exponent nCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 155 / 303
  • 471. Log-Distance Path Loss Models 1 The average large scale path loss for an arbitrary T-R separation is expressed as a function of distance using a path loss exponent n 2 The value of n characteristics the propagation environment n d PL (d) ∝ d ≥ d0 (24) d0 Which refers the average large-scale path loss at a distance d (dB) d PL (dB) = PL (d0 ) + 10n log (25) d0 Which refers free space propagation model between transmitter and d0Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 155 / 303
  • 472. Log-Distance Path Loss Models 1 The average large scale path loss for an arbitrary T-R separation is expressed as a function of distance using a path loss exponent n 2 The value of n characteristics the propagation environment For free space it is 2 n d PL (d) ∝ d ≥ d0 (24) d0 Which refers the average large-scale path loss at a distance d (dB) d PL (dB) = PL (d0 ) + 10n log (25) d0 Which refers free space propagation model between transmitter and d0Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 155 / 303
  • 473. Log-Distance Path Loss Models 1 The average large scale path loss for an arbitrary T-R separation is expressed as a function of distance using a path loss exponent n 2 The value of n characteristics the propagation environment For free space it is 2 It will be large when we have many obstructions n d PL (d) ∝ d ≥ d0 (24) d0 Which refers the average large-scale path loss at a distance d (dB) d PL (dB) = PL (d0 ) + 10n log (25) d0 Which refers free space propagation model between transmitter and d0Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 155 / 303
  • 474. Large Scale Path Loss for different EnvironmentsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 156 / 303
  • 475. Log-Normal Shadowing 1 The Log-Distance model path loss equation does not consider the fact that the surrounding environment may be vastly different at two locations having the same T-R separationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 157 / 303
  • 476. Log-Normal Shadowing 1 The Log-Distance model path loss equation does not consider the fact that the surrounding environment may be vastly different at two locations having the same T-R separation 2 This leads to measurements that are different than the predicted average values obtained using the equationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 157 / 303
  • 477. Log-Normal Shadowing 1 The Log-Distance model path loss equation does not consider the fact that the surrounding environment may be vastly different at two locations having the same T-R separation 2 This leads to measurements that are different than the predicted average values obtained using the equation 3 Measurements show that for any value d, the path loss PL (d) in dBm at a location is random and distributed log-normallyCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 157 / 303
  • 478. Log-Normal Shadowing 1 The Log-Distance model path loss equation does not consider the fact that the surrounding environment may be vastly different at two locations having the same T-R separation 2 This leads to measurements that are different than the predicted average values obtained using the equation 3 Measurements show that for any value d, the path loss PL (d) in dBm at a location is random and distributed log-normally 4 To take into account the shadowing effects due to cluttering on the propagation path, a factor is added as follows PL (d) [dB] = PL (d) + Xσ (26) where Xσ is the correction factor which is distributed log-normally d PL (d) [dB] = PL (d0 ) + 10n log + Xσ (27) d0Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 157 / 303
  • 479. Log-Normal Shadowing 1 Xσ is a zero mean Gaussian distributed random variable (in dB) with S.D σ (dB) Pr (d) [dBm] = Pt [dBm] − PL (d) [dB] (28) d Pr (d) [dBm] = Pt [dBm] − PL (d0 ) [dB] + 10n log + Xσ d0 (29) The pdf of the received signal is given by 1 (M − M)2 P(M) = √ e− (30) 2πσ 2σ 2 where M is the true received signal M is the area average signal level σ is the SD in dBCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 158 / 303
  • 480. Example 1 Let Pr (d0 ) = 0 dBm at d0 =100 mCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 159 / 303
  • 481. Example 1 Let Pr (d0 ) = 0 dBm at d0 =100 m 2 The following table gives the measured values of received power Pr at various distances Distance from Transmitter Received Power 100 m 0 dBm 500 m -15 dBm 1000 m -21 dBm 3000 m -38 dBmCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 159 / 303
  • 482. Example 1 Let Pr (d0 ) = 0 dBm at d0 =100 m 2 The following table gives the measured values of received power Pr at various distances Distance from Transmitter Received Power 100 m 0 dBm 500 m -15 dBm 1000 m -21 dBm 3000 m -38 dBm 3 Compute the estimates for received power at different distances using long-distance path loss model d PL dB = PL (d0 ) + 10n log (31) d0Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 159 / 303
  • 483. Example 1 Since Pr (d0 ) = 0 dBm, the equation reduces to d PL dB = 0 + 10n log (32) d0Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 160 / 303
  • 484. Example 1 Since Pr (d0 ) = 0 dBm, the equation reduces to d PL dB = 0 + 10n log (32) d0 2 Using this equation to compute estimates of power levels at d =500 m, d=1000 m and 3000 m Distance Measured Pr (dBm) Estimated Pr (dBm) 100 m 0 0 500 m -15 -6.99 n 1000 m -21 -10 n 3000 m -36 -14.77 nCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 160 / 303
  • 485. Example 1 Now calculate the mean square error (MSE) between the estimated and measured value and choose a value of n such that MSE is minimizedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 161 / 303
  • 486. Example 1 Now calculate the mean square error (MSE) between the estimated and measured value and choose a value of n such that MSE is minimized 2 Mean Square Error : K MSE = ˆ2 (Pi − Pi ) (33) i=1 Pi ⇒ Actual measured value of power at some distance ˆ Pi ) ⇒ = Estimate of power at that distance K ⇒ = no.of measured samplesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 161 / 303
  • 487. Example 1 (MSE )2 = 0 + (6.99n − 5)2 + (10n − 11)2 + (14.77n − 16)2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 162 / 303
  • 488. Example 1 (MSE )2 = 0 + (6.99n − 5)2 + (10n − 11)2 + (14.77n − 16)2 2 Note that MSE is a function of nCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 162 / 303
  • 489. Example 1 (MSE )2 = 0 + (6.99n − 5)2 + (10n − 11)2 + (14.77n − 16)2 2 Note that MSE is a function of n d 3 Minimization of MSE(n) is to find (MSE (n)) =0 dnCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 162 / 303
  • 490. Example 1 Sample variance calculation (σ 2 ) K ˆ2 (Pi − Pi ) i=1 σ2 = (34) K σ 2 = MSE(N)/K σ 2 = MMSE/K MMSE σ= KCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 163 / 303
  • 491. Example 1 Sample variance calculation (σ 2 ) K ˆ2 (Pi − Pi ) i=1 σ2 = (34) K σ 2 = MSE(N)/K σ 2 = MMSE/K MMSE σ= K 2 A Gaussian random variable having zero mean and variance σ 2 can be added to the Log-Distance path loss model to simulate the shadowing effects N is the value that minimizes MSE(n)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 163 / 303
  • 492. Outage Probability 1 The probability that the received power Pr (d) (in dB) at a distance d is above (or below) some fixed value γ ?Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 164 / 303
  • 493. Outage Probability 1 The probability that the received power Pr (d) (in dB) at a distance d is above (or below) some fixed value γ ? 2 That is Prob(Pr (d) >= γ) or prob (Pr (d) ≤ γ)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 164 / 303
  • 494. Outage Probability 1 The probability that the received power Pr (d) (in dB) at a distance d is above (or below) some fixed value γ ? 2 That is Prob(Pr (d) >= γ) or prob (Pr (d) ≤ γ) 3 For a normally distributed random variable, X ∞ (x − µ)2 1 − Pr (x > x0 ) = √ e 2σ 2 dx (35) x0 σ 2π µ ⇒ Mean σ ⇒ SD σ 2 ⇒ VarianceCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 164 / 303
  • 495. Outage ProbabilityCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 165 / 303
  • 496. Percentage of coverage area 1 Due to random effects of shadowing, some areas within the coverage area may be below a particular received signal thresholdCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 166 / 303
  • 497. Percentage of coverage area 1 Due to random effects of shadowing, some areas within the coverage area may be below a particular received signal threshold 2 It is useful to compute the percentage of coverage area within the boundary of the cellCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 166 / 303
  • 498. Percentage of coverage area 1 Due to random effects of shadowing, some areas within the coverage area may be below a particular received signal threshold 2 It is useful to compute the percentage of coverage area within the boundary of the cell 3 Consider a circular coverage area with radius R from a BS and a minimum threshold power level γCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 166 / 303
  • 499. Percentage of coverage area 1 Due to random effects of shadowing, some areas within the coverage area may be below a particular received signal threshold 2 It is useful to compute the percentage of coverage area within the boundary of the cell 3 Consider a circular coverage area with radius R from a BS and a minimum threshold power level γ 4 We need to find the percentage of area where the received signal level greater than or equal to γCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 166 / 303
  • 500. Percentage of coverage area 1 The percentage area is given by 1 PA (γ) = P [Pr (r ) > γdA] (36) πR 3 2π R 1 PA (γ) = P [Pr (r ) > γ] r dr dθ (37) πR 3 0 0Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 167 / 303
  • 501. Percentage of coverage area 1 The percentage area is given by 1 PA (γ) = P [Pr (r ) > γdA] (36) πR 3 2π R 1 PA (γ) = P [Pr (r ) > γ] r dr dθ (37) πR 3 0 0 2 P [Pr (r ) > γ] is the probability that the received power at a distance d=r is greater than γ and is constant within the incrementally small area dA 1 1 γ − Pr (d) P [Pr (γ) > γ] = − erf √ (38) 2 2 σ 2 2 z 2 Where erf(z) = √ 0 e −x dx πCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 167 / 303
  • 502. Percentage of coverage area 1 The path loss at a distance d(PL (d)) can be written as PL (0 to d) = PL (0 to d0 ) + PL (d0 to R) − PL (d to R) (39) where d0 is a free space reference distance (r¿d0 ) R d PL (d) = PL (d0 ) + 10n log + 10n log (40) d0 R Substituting equation 38 in equation 40 we get 1 1 P [Pr (r ) > γ] = − erf 2 2 σ r    γ − Pr − (PL (d0 )) + 10n log d0 + 10n log R  (41)  √   σ 2 Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 168 / 303
  • 503. Percentage of coverage area 1 Further simplifying we get 1 − 2ab   1  1 − ab PA (γ) = − 1 − erf (a) + e b 2 1 − erf  2 b (42) R    γ − Pr + PL (d0 ) + 10n log d0  where a =  √   σ 2  10n loge b= √ σ 2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 169 / 303
  • 504. Family of curves for percentage of coverage areaCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 170 / 303
  • 505. Family of curves for percentage of coverage areaCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 171 / 303
  • 506. Outdoor Propagation Models 1 Depending on the coverage area, outdoor propagation environments may be divided into three categoriesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 172 / 303
  • 507. Outdoor Propagation Models 1 Depending on the coverage area, outdoor propagation environments may be divided into three categories Propagation in macro cellsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 172 / 303
  • 508. Outdoor Propagation Models 1 Depending on the coverage area, outdoor propagation environments may be divided into three categories Propagation in macro cells Propagation in micro cellsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 172 / 303
  • 509. Outdoor Propagation Models 1 Depending on the coverage area, outdoor propagation environments may be divided into three categories Propagation in macro cells Propagation in micro cells Propagation in street micro-cellsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 172 / 303
  • 510. Macro-cells 1 BS located at high pointsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 173 / 303
  • 511. Macro-cells 1 BS located at high points 2 Coverage of several kilometreCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 173 / 303
  • 512. Macro-cells 1 BS located at high points 2 Coverage of several kilometre 3 The average path loss in dB has normal distributionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 173 / 303
  • 513. Macro-cells 1 BS located at high points 2 Coverage of several kilometre 3 The average path loss in dB has normal distribution 4 Average path loss is a result of many forward scatterings over a large number of obstaclesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 173 / 303
  • 514. Macro-cells 1 BS located at high points 2 Coverage of several kilometre 3 The average path loss in dB has normal distribution 4 Average path loss is a result of many forward scatterings over a large number of obstacles Each containing a random multiplicative factor and converted to dB gives the sum of random variableCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 173 / 303
  • 515. Macro-cells 1 BS located at high points 2 Coverage of several kilometre 3 The average path loss in dB has normal distribution 4 Average path loss is a result of many forward scatterings over a large number of obstacles Each containing a random multiplicative factor and converted to dB gives the sum of random variable 5 Sum is normally distributed because of central limit theoremCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 173 / 303
  • 516. Micro-cells 1 Propagation differs significantlyCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 174 / 303
  • 517. Micro-cells 1 Propagation differs significantly Milder propagation characteristicsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 174 / 303
  • 518. Micro-cells 1 Propagation differs significantly Milder propagation characteristics Small multipath delay spread and shallow fading imply the feasibility of higher data rate transmissionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 174 / 303
  • 519. Micro-cells 1 Propagation differs significantly Milder propagation characteristics Small multipath delay spread and shallow fading imply the feasibility of higher data rate transmission 2 Mostly used in crowded urban areasCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 174 / 303
  • 520. Micro-cells 1 Propagation differs significantly Milder propagation characteristics Small multipath delay spread and shallow fading imply the feasibility of higher data rate transmission 2 Mostly used in crowded urban areas 3 If the transmitter antenna is lower than the buildings then signals propagate along the streets : street micro-cellsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 174 / 303
  • 521. Street Micro-cells 1 Most of the signal propagates along the streetCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 175 / 303
  • 522. Street Micro-cells 1 Most of the signal propagates along the street 2 The signal may reach with LOS paths if the receiver is along the same street with the transmitterCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 175 / 303
  • 523. Street Micro-cells 1 Most of the signal propagates along the street 2 The signal may reach with LOS paths if the receiver is along the same street with the transmitter 3 The signals may reach via indirect propagation mechanisms if the receiver turns to another streetCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 175 / 303
  • 524. Street Micro-cellsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 176 / 303
  • 525. Macro-cells Vs Micro-cells Macro cell Micro cell Cell Radius 1 to 20 km 0.1 to 1 km Transmit Power 1 to 10 W 0.1 to 1 W Fading Rayleigh Nakgami-Rice RMS Delay Spread 0.1 to 10 µs 10 to 100 ns Maximum Bit Rate 0.3 Mbps 1 MbpsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 177 / 303
  • 526. Outdoor Propagation Models 1 Longely-Rice ModelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 178 / 303
  • 527. Outdoor Propagation Models 1 Longely-Rice Model 2 Okumura ModelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 178 / 303
  • 528. Outdoor Propagation Models 1 Longely-Rice Model 2 Okumura Model 3 Hata ModelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 178 / 303
  • 529. Outdoor Propagation Models 1 Longely-Rice Model 2 Okumura Model 3 Hata Model 4 PCS extension to Hata ModelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 178 / 303
  • 530. Outdoor Propagation Models 1 Longely-Rice Model 2 Okumura Model 3 Hata Model 4 PCS extension to Hata Model 5 Wideband PCS Microcell ModelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 178 / 303
  • 531. Outdoor Propagation Models 1 Takes place over irregular terrainCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 179 / 303
  • 532. Outdoor Propagation Models 1 Takes place over irregular terrain 2 Terrain profile must be taken into consideration for estimating path lossCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 179 / 303
  • 533. Outdoor Propagation Models 1 Takes place over irregular terrain 2 Terrain profile must be taken into consideration for estimating path loss 3 Trees, buildings, hills etc must be taken into considerationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 179 / 303
  • 534. Longely-Rice Model 1 Applicable to point-to-point communicationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 180 / 303
  • 535. Longely-Rice Model 1 Applicable to point-to-point communication 2 It covers 40 MHz to 100 GHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 180 / 303
  • 536. Longely-Rice Model 1 Applicable to point-to-point communication 2 It covers 40 MHz to 100 GHz 3 It also accounts for a wide range of terrainsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 180 / 303
  • 537. Longely-Rice Model 1 Applicable to point-to-point communication 2 It covers 40 MHz to 100 GHz 3 It also accounts for a wide range of terrains 4 Path geometry of the terrain and the refractivity of the troposphere is used for calculationsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 180 / 303
  • 538. Longely-Rice Model 1 Applicable to point-to-point communication 2 It covers 40 MHz to 100 GHz 3 It also accounts for a wide range of terrains 4 Path geometry of the terrain and the refractivity of the troposphere is used for calculations 5 Geometrical optics is used along with two ray ground reflection modelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 180 / 303
  • 539. Longely-Rice Model 1 Available as a computer program that takes the following as inputCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 181 / 303
  • 540. Longely-Rice Model 1 Available as a computer program that takes the following as input Transmission frequencyCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 181 / 303
  • 541. Longely-Rice Model 1 Available as a computer program that takes the following as input Transmission frequency Path lengthCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 181 / 303
  • 542. Longely-Rice Model 1 Available as a computer program that takes the following as input Transmission frequency Path length PolarizationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 181 / 303
  • 543. Longely-Rice Model 1 Available as a computer program that takes the following as input Transmission frequency Path length Polarization Antenna heightCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 181 / 303
  • 544. Longely-Rice Model 1 Available as a computer program that takes the following as input Transmission frequency Path length Polarization Antenna height Surface reflectivityCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 181 / 303
  • 545. Longely-Rice Model 1 Available as a computer program that takes the following as input Transmission frequency Path length Polarization Antenna height Surface reflectivity Ground conductivity and dielectric constantCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 181 / 303
  • 546. Longely-Rice Model 1 Available as a computer program that takes the following as input Transmission frequency Path length Polarization Antenna height Surface reflectivity Ground conductivity and dielectric constant Climatic factorsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 181 / 303
  • 547. Longely-Rice Model 1 Available as a computer program that takes the following as input Transmission frequency Path length Polarization Antenna height Surface reflectivity Ground conductivity and dielectric constant Climatic factors 2 Does not take into the account of the buildings and foliageCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 181 / 303
  • 548. Okumura Model 1 Most widely used model for signal prediction in urban areasCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 182 / 303
  • 549. Okumura Model 1 Most widely used model for signal prediction in urban areas 2 In early days, the models were based on empirical studiesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 182 / 303
  • 550. Okumura Model 1 Most widely used model for signal prediction in urban areas 2 In early days, the models were based on empirical studies 3 This model is purely based on measurementsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 182 / 303
  • 551. Okumura Model 1 Most widely used model for signal prediction in urban areas 2 In early days, the models were based on empirical studies 3 This model is purely based on measurements 4 Okumura found that a good model for path loss was a simple power law where the exponent n is a function of frequency, antenna height etc..Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 182 / 303
  • 552. Okumura Model 1 Most widely used model for signal prediction in urban areas 2 In early days, the models were based on empirical studies 3 This model is purely based on measurements 4 Okumura found that a good model for path loss was a simple power law where the exponent n is a function of frequency, antenna height etc.. 5 It is applicable toCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 182 / 303
  • 553. Okumura Model 1 Most widely used model for signal prediction in urban areas 2 In early days, the models were based on empirical studies 3 This model is purely based on measurements 4 Okumura found that a good model for path loss was a simple power law where the exponent n is a function of frequency, antenna height etc.. 5 It is applicable to Frequencies : 150 MHz to 1920 M HzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 182 / 303
  • 554. Okumura Model 1 Most widely used model for signal prediction in urban areas 2 In early days, the models were based on empirical studies 3 This model is purely based on measurements 4 Okumura found that a good model for path loss was a simple power law where the exponent n is a function of frequency, antenna height etc.. 5 It is applicable to Frequencies : 150 MHz to 1920 M Hz Can be extrapolated upto 3 GHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 182 / 303
  • 555. Okumura Model 1 Most widely used model for signal prediction in urban areas 2 In early days, the models were based on empirical studies 3 This model is purely based on measurements 4 Okumura found that a good model for path loss was a simple power law where the exponent n is a function of frequency, antenna height etc.. 5 It is applicable to Frequencies : 150 MHz to 1920 M Hz Can be extrapolated upto 3 GHz Distances : 1 km to 100 kmCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 182 / 303
  • 556. Okumura Model 1 Okumura developed a set of curves giving the medium attenuation relative to free space in an urban area over quasi-smooth terrainCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 183 / 303
  • 557. Okumura Model 1 Okumura developed a set of curves giving the medium attenuation relative to free space in an urban area over quasi-smooth terrain 2 Okumura can be expressed as L50 (d) (dB) = LF (d)+Amu (f , d)−G (hte )−G (hre )−GAREA (43)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 183 / 303
  • 558. Okumura Model 1 Okumura developed a set of curves giving the medium attenuation relative to free space in an urban area over quasi-smooth terrain 2 Okumura can be expressed as L50 (d) (dB) = LF (d)+Amu (f , d)−G (hte )−G (hre )−GAREA (43) L50 : 50th percentile of path lossCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 183 / 303
  • 559. Okumura Model 1 Okumura developed a set of curves giving the medium attenuation relative to free space in an urban area over quasi-smooth terrain 2 Okumura can be expressed as L50 (d) (dB) = LF (d)+Amu (f , d)−G (hte )−G (hre )−GAREA (43) L50 : 50th percentile of path loss LF (d) : Free space propagation path lossCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 183 / 303
  • 560. Okumura Model 1 Okumura developed a set of curves giving the medium attenuation relative to free space in an urban area over quasi-smooth terrain 2 Okumura can be expressed as L50 (d) (dB) = LF (d)+Amu (f , d)−G (hte )−G (hre )−GAREA (43) L50 : 50th percentile of path loss LF (d) : Free space propagation path loss Amufd : Median attenuation relative to free spaceCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 183 / 303
  • 561. Okumura Model 1 Okumura developed a set of curves giving the medium attenuation relative to free space in an urban area over quasi-smooth terrain 2 Okumura can be expressed as L50 (d) (dB) = LF (d)+Amu (f , d)−G (hte )−G (hre )−GAREA (43) L50 : 50th percentile of path loss LF (d) : Free space propagation path loss Amufd : Median attenuation relative to free space G (hte ) : BS antenna height gain factorCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 183 / 303
  • 562. Okumura Model 1 Okumura developed a set of curves giving the medium attenuation relative to free space in an urban area over quasi-smooth terrain 2 Okumura can be expressed as L50 (d) (dB) = LF (d)+Amu (f , d)−G (hte )−G (hre )−GAREA (43) L50 : 50th percentile of path loss LF (d) : Free space propagation path loss Amufd : Median attenuation relative to free space G (hte ) : BS antenna height gain factor G (hre ) : Mobile antenna height gain factorCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 183 / 303
  • 563. Okumura Model 1 Okumura developed a set of curves giving the medium attenuation relative to free space in an urban area over quasi-smooth terrain 2 Okumura can be expressed as L50 (d) (dB) = LF (d)+Amu (f , d)−G (hte )−G (hre )−GAREA (43) L50 : 50th percentile of path loss LF (d) : Free space propagation path loss Amufd : Median attenuation relative to free space G (hte ) : BS antenna height gain factor G (hre ) : Mobile antenna height gain factor GAREA : Gain due to the type of environmentCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 183 / 303
  • 564. Okumura Model 1 The following illustrates the calculation hte G (hte ) = 20 log 1000m > hte > 30m 200 hre G (hre ) = 10 log hre ≤ 3m (44) 3 hre G (hre ) = 20 log 10m > hre > 3m 3Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 184 / 303
  • 565. Okumura Model Figure: Median Attenuation versus FrequencyCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 185 / 303
  • 566. Okumura Model Figure: Correction Factor GAREA versus FrequencyCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 186 / 303
  • 567. Okumura Model-Example 1 Suppose we want to calculate the median path loss relative to the free space loss at a distance of 50 km. The BS height is 200 m and the MS height is 3m. The frequency of operation is 1 GHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 187 / 303
  • 568. Okumura Model-Example 1 Suppose we want to calculate the median path loss relative to the free space loss at a distance of 50 km. The BS height is 200 m and the MS height is 3m. The frequency of operation is 1 GHz 2 By looking into the curve we can calculate the value of medium attenuation to be 45 dBCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 187 / 303
  • 569. Okumura Model 1 It is wholly based on measured dataCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 188 / 303
  • 570. Okumura Model 1 It is wholly based on measured data 2 No analytical explanationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 188 / 303
  • 571. Okumura Model 1 It is wholly based on measured data 2 No analytical explanation 3 In certain areas the curve can be extrapolatedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 188 / 303
  • 572. Okumura Model 1 It is wholly based on measured data 2 No analytical explanation 3 In certain areas the curve can be extrapolated 4 Simplest and most accurate path loss prediction modelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 188 / 303
  • 573. Okumura Model 1 It is wholly based on measured data 2 No analytical explanation 3 In certain areas the curve can be extrapolated 4 Simplest and most accurate path loss prediction model 5 Typical S.D between predicted and measured path loss values are between 10 dB to 14 dBCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 188 / 303
  • 574. Hata Model 1 The Hata model is the empirical formulation of the graphical path loss data provided by okumura and is valid from 150 MHz to 1.5 GHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 189 / 303
  • 575. Hata Model 1 The Hata model is the empirical formulation of the graphical path loss data provided by okumura and is valid from 150 MHz to 1.5 GHz 2 The median path loss in urban areas is given by L50 (dB) = 69.55 + 26.16logfc (MHz) − 13.82 log hte − a(hre ) +(44.9 − 6.55 log hte ) log d (45) Where fc is the frequency in MHz hte is the BS antenna height ( 30 m to 200 m ) hre is the mobile antenna height ( 1 m to 10 m ) d is the T-R separation in km a(hre ) is the correction factor for effective mobile antenna height which is a function of coverage areaCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 189 / 303
  • 576. Hata Model 1 Urban area: a(hre ) = 8.29(log 1.54hre )2 − 1.1dB for fc ≤ 300MHz (46) a [hre (m)] = 3.2(log 11.75hre )2 − 4.97dB for fc ≥ 300MHz (47)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 190 / 303
  • 577. Hata Model 1 Urban area: a(hre ) = 8.29(log 1.54hre )2 − 1.1dB for fc ≤ 300MHz (46) a [hre (m)] = 3.2(log 11.75hre )2 − 4.97dB for fc ≥ 300MHz (47) 2 Sub-urban area: 2 fc L50 (dB) = L50 (urban) − 2 log − 5.4 (48) 28Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 190 / 303
  • 578. Hata Model 1 Urban area: a(hre ) = 8.29(log 1.54hre )2 − 1.1dB for fc ≤ 300MHz (46) a [hre (m)] = 3.2(log 11.75hre )2 − 4.97dB for fc ≥ 300MHz (47) 2 Sub-urban area: 2 fc L50 (dB) = L50 (urban) − 2 log − 5.4 (48) 28 3 Open area: L50 (dB) = L50 (urban)−4.78 (log fc )2 +18.23 log fc −40.94 (49)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 190 / 303
  • 579. PCS Extension to Hata Model 1 Hata model is extended to 2 GHz L50 (urban) = 46.3 + 33.9 log fc − 13.82 log hte − a(hre ) (50) +(44.9 − 6.55 log hte ) log d + CM CM = 0 db for medium sized city and sun-urban areas CM = 3 db for for metropolitan centresCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 191 / 303
  • 580. PCS Extension to Hata Model 1 Hata model is extended to 2 GHz L50 (urban) = 46.3 + 33.9 log fc − 13.82 log hte − a(hre ) (50) +(44.9 − 6.55 log hte ) log d + CM CM = 0 db for medium sized city and sun-urban areas CM = 3 db for for metropolitan centres 2 It is restricted to the following range of parametersCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 191 / 303
  • 581. PCS Extension to Hata Model 1 Hata model is extended to 2 GHz L50 (urban) = 46.3 + 33.9 log fc − 13.82 log hte − a(hre ) (50) +(44.9 − 6.55 log hte ) log d + CM CM = 0 db for medium sized city and sun-urban areas CM = 3 db for for metropolitan centres 2 It is restricted to the following range of parameters f ⇒ 1500 MHz to 2000 M HzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 191 / 303
  • 582. PCS Extension to Hata Model 1 Hata model is extended to 2 GHz L50 (urban) = 46.3 + 33.9 log fc − 13.82 log hte − a(hre ) (50) +(44.9 − 6.55 log hte ) log d + CM CM = 0 db for medium sized city and sun-urban areas CM = 3 db for for metropolitan centres 2 It is restricted to the following range of parameters f ⇒ 1500 MHz to 2000 M Hz hte ⇒ 30 m to 200 mCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 191 / 303
  • 583. PCS Extension to Hata Model 1 Hata model is extended to 2 GHz L50 (urban) = 46.3 + 33.9 log fc − 13.82 log hte − a(hre ) (50) +(44.9 − 6.55 log hte ) log d + CM CM = 0 db for medium sized city and sun-urban areas CM = 3 db for for metropolitan centres 2 It is restricted to the following range of parameters f ⇒ 1500 MHz to 2000 M Hz hte ⇒ 30 m to 200 m hre ⇒ 1 m to 10 mCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 191 / 303
  • 584. PCS Extension to Hata Model 1 Hata model is extended to 2 GHz L50 (urban) = 46.3 + 33.9 log fc − 13.82 log hte − a(hre ) (50) +(44.9 − 6.55 log hte ) log d + CM CM = 0 db for medium sized city and sun-urban areas CM = 3 db for for metropolitan centres 2 It is restricted to the following range of parameters f ⇒ 1500 MHz to 2000 M Hz hte ⇒ 30 m to 200 m hre ⇒ 1 m to 10 m d ⇒ 1 km to 20 kmCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 191 / 303
  • 585. Indoor Propagation 1 It is based on measured dataCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 192 / 303
  • 586. Indoor Propagation 1 It is based on measured data 2 Indoor channels are different from traditional mobile radio channels in two different waysCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 192 / 303
  • 587. Indoor Propagation 1 It is based on measured data 2 Indoor channels are different from traditional mobile radio channels in two different ways The distance covered are much smallerCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 192 / 303
  • 588. Indoor Propagation 1 It is based on measured data 2 Indoor channels are different from traditional mobile radio channels in two different ways The distance covered are much smaller The variability of the environment is much greater for a much smaller range of T-R separation distancesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 192 / 303
  • 589. Indoor Propagation 1 It is based on measured data 2 Indoor channels are different from traditional mobile radio channels in two different ways The distance covered are much smaller The variability of the environment is much greater for a much smaller range of T-R separation distances 3 The propagation inside a building is influenced byCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 192 / 303
  • 590. Indoor Propagation 1 It is based on measured data 2 Indoor channels are different from traditional mobile radio channels in two different ways The distance covered are much smaller The variability of the environment is much greater for a much smaller range of T-R separation distances 3 The propagation inside a building is influenced by Layout of the buildingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 192 / 303
  • 591. Indoor Propagation 1 It is based on measured data 2 Indoor channels are different from traditional mobile radio channels in two different ways The distance covered are much smaller The variability of the environment is much greater for a much smaller range of T-R separation distances 3 The propagation inside a building is influenced by Layout of the building Construction materialsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 192 / 303
  • 592. Indoor Propagation 1 It is based on measured data 2 Indoor channels are different from traditional mobile radio channels in two different ways The distance covered are much smaller The variability of the environment is much greater for a much smaller range of T-R separation distances 3 The propagation inside a building is influenced by Layout of the building Construction materials Building type : office area, residential area, factory etc.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 192 / 303
  • 593. Indoor Propagation 1 It is based on measured data 2 Indoor channels are different from traditional mobile radio channels in two different ways The distance covered are much smaller The variability of the environment is much greater for a much smaller range of T-R separation distances 3 The propagation inside a building is influenced by Layout of the building Construction materials Building type : office area, residential area, factory etc. 4 Indoor Propagation is dominated by the same mechanism as outdoor: reflection , scattering and diffractionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 192 / 303
  • 594. Indoor Propagation 1 However the conditions are more variable in indoor propagationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 193 / 303
  • 595. Indoor Propagation 1 However the conditions are more variable in indoor propagation Doors/Windows open or notCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 193 / 303
  • 596. Indoor Propagation 1 However the conditions are more variable in indoor propagation Doors/Windows open or not The mounting place of antennaCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 193 / 303
  • 597. Indoor Propagation 1 However the conditions are more variable in indoor propagation Doors/Windows open or not The mounting place of antenna The level of floorsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 193 / 303
  • 598. Indoor Propagation 1 However the conditions are more variable in indoor propagation Doors/Windows open or not The mounting place of antenna The level of floors 2 The indoor channels are classified asCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 193 / 303
  • 599. Indoor Propagation 1 However the conditions are more variable in indoor propagation Doors/Windows open or not The mounting place of antenna The level of floors 2 The indoor channels are classified as Line of sight LOSCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 193 / 303
  • 600. Indoor Propagation 1 However the conditions are more variable in indoor propagation Doors/Windows open or not The mounting place of antenna The level of floors 2 The indoor channels are classified as Line of sight LOS Obstructed with varying degrees of clutterCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 193 / 303
  • 601. Indoor Propagation 1 However the conditions are more variable in indoor propagation Doors/Windows open or not The mounting place of antenna The level of floors 2 The indoor channels are classified as Line of sight LOS Obstructed with varying degrees of clutter 3 Building typesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 193 / 303
  • 602. Indoor Propagation 1 However the conditions are more variable in indoor propagation Doors/Windows open or not The mounting place of antenna The level of floors 2 The indoor channels are classified as Line of sight LOS Obstructed with varying degrees of clutter 3 Building types Open plain buildings with movable wall panelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 193 / 303
  • 603. Indoor Propagation 1 However the conditions are more variable in indoor propagation Doors/Windows open or not The mounting place of antenna The level of floors 2 The indoor channels are classified as Line of sight LOS Obstructed with varying degrees of clutter 3 Building types Open plain buildings with movable wall panels Factory buildingsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 193 / 303
  • 604. Indoor Propagation 1 However the conditions are more variable in indoor propagation Doors/Windows open or not The mounting place of antenna The level of floors 2 The indoor channels are classified as Line of sight LOS Obstructed with varying degrees of clutter 3 Building types Open plain buildings with movable wall panels Factory buildings Grocery storesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 193 / 303
  • 605. Indoor Propagation 1 However the conditions are more variable in indoor propagation Doors/Windows open or not The mounting place of antenna The level of floors 2 The indoor channels are classified as Line of sight LOS Obstructed with varying degrees of clutter 3 Building types Open plain buildings with movable wall panels Factory buildings Grocery stores Retail storesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 193 / 303
  • 606. Indoor Propagation 1 However the conditions are more variable in indoor propagation Doors/Windows open or not The mounting place of antenna The level of floors 2 The indoor channels are classified as Line of sight LOS Obstructed with varying degrees of clutter 3 Building types Open plain buildings with movable wall panels Factory buildings Grocery stores Retail stores Sports arenasCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 193 / 303
  • 607. Indoor Propagation 1 Temporal fading for fixed and moving terminalsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 194 / 303
  • 608. Indoor Propagation 1 Temporal fading for fixed and moving terminals Motion of people inside building causes Ricean fading for the stationary receiversCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 194 / 303
  • 609. Indoor Propagation 1 Temporal fading for fixed and moving terminals Motion of people inside building causes Ricean fading for the stationary receivers Portable receivers experience in generalCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 194 / 303
  • 610. Indoor Propagation 1 Temporal fading for fixed and moving terminals Motion of people inside building causes Ricean fading for the stationary receivers Portable receivers experience in general 1 Rayleigh fading for OBS propagation’Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 194 / 303
  • 611. Indoor Propagation 1 Temporal fading for fixed and moving terminals Motion of people inside building causes Ricean fading for the stationary receivers Portable receivers experience in general 1 Rayleigh fading for OBS propagation’ 2 Ricean fading for LOS pathsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 194 / 303
  • 612. Indoor Propagation 1 Temporal fading for fixed and moving terminals Motion of people inside building causes Ricean fading for the stationary receivers Portable receivers experience in general 1 Rayleigh fading for OBS propagation’ 2 Ricean fading for LOS paths 2 Multipath delay spreadCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 194 / 303
  • 613. Indoor Propagation 1 Temporal fading for fixed and moving terminals Motion of people inside building causes Ricean fading for the stationary receivers Portable receivers experience in general 1 Rayleigh fading for OBS propagation’ 2 Ricean fading for LOS paths 2 Multipath delay spread Buildings with fewer metals and hard portions typically have small RMS delay spreads : 30 to 60 nsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 194 / 303
  • 614. Indoor Propagation 1 Temporal fading for fixed and moving terminals Motion of people inside building causes Ricean fading for the stationary receivers Portable receivers experience in general 1 Rayleigh fading for OBS propagation’ 2 Ricean fading for LOS paths 2 Multipath delay spread Buildings with fewer metals and hard portions typically have small RMS delay spreads : 30 to 60 ns 1 Can support data rates excess of several Mbps without equalizationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 194 / 303
  • 615. Indoor Propagation 1 Temporal fading for fixed and moving terminals Motion of people inside building causes Ricean fading for the stationary receivers Portable receivers experience in general 1 Rayleigh fading for OBS propagation’ 2 Ricean fading for LOS paths 2 Multipath delay spread Buildings with fewer metals and hard portions typically have small RMS delay spreads : 30 to 60 ns 1 Can support data rates excess of several Mbps without equalization 3 Larger buildings with great amount of metal and open aisles may have RMS delay spreads as large as 300 nsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 194 / 303
  • 616. Indoor Propagation 1 Temporal fading for fixed and moving terminals Motion of people inside building causes Ricean fading for the stationary receivers Portable receivers experience in general 1 Rayleigh fading for OBS propagation’ 2 Ricean fading for LOS paths 2 Multipath delay spread Buildings with fewer metals and hard portions typically have small RMS delay spreads : 30 to 60 ns 1 Can support data rates excess of several Mbps without equalization 3 Larger buildings with great amount of metal and open aisles may have RMS delay spreads as large as 300 ns 1 Cannot support data rates more than a few hundred kbps without equalizationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 194 / 303
  • 617. Indoor Propagation 1 Path LossCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 195 / 303
  • 618. Indoor Propagation 1 Path Loss The following equation describes the indoor path loss d PL (dB) = PL (d0 ) + 10n log + Xσ (51) d0Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 195 / 303
  • 619. Indoor Propagation 1 Path Loss The following equation describes the indoor path loss d PL (dB) = PL (d0 ) + 10n log + Xσ (51) d0 n and σ depend upon the type of buildingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 195 / 303
  • 620. Indoor Propagation 1 Path Loss The following equation describes the indoor path loss d PL (dB) = PL (d0 ) + 10n log + Xσ (51) d0 n and σ depend upon the type of building Smaller value of σ indicates better accuracy of the path loss modelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 195 / 303
  • 621. Indoor Propagation 1 Path Loss The following equation describes the indoor path loss d PL (dB) = PL (d0 ) + 10n log + Xσ (51) d0 n and σ depend upon the type of building Smaller value of σ indicates better accuracy of the path loss model 2 In building path loss factorsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 195 / 303
  • 622. Indoor Propagation 1 Path Loss The following equation describes the indoor path loss d PL (dB) = PL (d0 ) + 10n log + Xσ (51) d0 n and σ depend upon the type of building Smaller value of σ indicates better accuracy of the path loss model 2 In building path loss factors 1 Partition losses (same floor)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 195 / 303
  • 623. Indoor Propagation 1 Path Loss The following equation describes the indoor path loss d PL (dB) = PL (d0 ) + 10n log + Xσ (51) d0 n and σ depend upon the type of building Smaller value of σ indicates better accuracy of the path loss model 2 In building path loss factors 1 Partition losses (same floor) 2 Partition losses between floorsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 195 / 303
  • 624. Indoor Propagation 1 Path Loss The following equation describes the indoor path loss d PL (dB) = PL (d0 ) + 10n log + Xσ (51) d0 n and σ depend upon the type of building Smaller value of σ indicates better accuracy of the path loss model 2 In building path loss factors 1 Partition losses (same floor) 2 Partition losses between floors 3 Signal penetration into buildingsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 195 / 303
  • 625. Path Losses (Same Floor) 1 Two kindsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 196 / 303
  • 626. Path Losses (Same Floor) 1 Two kinds 1 Hard partitions : Wall of the roomsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 196 / 303
  • 627. Path Losses (Same Floor) 1 Two kinds 1 Hard partitions : Wall of the rooms 2 Soft partitions : Movable partitions that do not span to the ceilingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 196 / 303
  • 628. Path Losses (Same Floor) 1 Two kinds 1 Hard partitions : Wall of the rooms 2 Soft partitions : Movable partitions that do not span to the ceiling 2 Path loss depends on the type of partitionsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 196 / 303
  • 629. Path Losses (Same Floor) Material Type Loss(dB) Frequency All metal partition 26 dB 815 MHz Concrete block wall 13 dB 1300 MHz Empty card board boxes 3-6 dB 1300 MHz Dry ply wood(o.75 inch) 1 dB 9.6 GHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 197 / 303
  • 630. Path Losses between Floors 1 External dimensions and materials of the buildingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 198 / 303
  • 631. Path Losses between Floors 1 External dimensions and materials of the building 2 Type of construction used to create floorsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 198 / 303
  • 632. Path Losses between Floors 1 External dimensions and materials of the building 2 Type of construction used to create floors 3 External surroundingsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 198 / 303
  • 633. Path Losses between Floors 1 External dimensions and materials of the building 2 Type of construction used to create floors 3 External surroundings 4 Number of windowsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 198 / 303
  • 634. Path Losses between Floors 1 External dimensions and materials of the building 2 Type of construction used to create floors 3 External surroundings 4 Number of windows 5 Presence of ting-ting on windows No.of Floors FAF(dB) Through 1 floor 12.9 Through 2 floors 18.7 Through 3 floors 24.4 Through 4 floors 27.6Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 198 / 303
  • 635. Path Losses between Floors 1 External dimensions and materials of the building 2 Type of construction used to create floors 3 External surroundings 4 Number of windows 5 Presence of ting-ting on windows No.of Floors FAF(dB) Through 1 floor 12.9 Through 2 floors 18.7 Through 3 floors 24.4 Through 4 floors 27.6 6 Average FAF in dB between floors of a building measured at 915 MHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 198 / 303
  • 636. Ericsson multiple break point model 1 Obtained by measurement in a multiple floor office buildingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 199 / 303
  • 637. Ericsson multiple break point model 1 Obtained by measurement in a multiple floor office building 2 The model has four break pointsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 199 / 303
  • 638. Ericsson multiple break point model 1 Obtained by measurement in a multiple floor office building 2 The model has four break points 3 Conducted at 900 MHzCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 199 / 303
  • 639. Attenuation Factor Model 1 Obtained by measurement in a multiple floor office building d PL (d)(dB) = PL (d0 )(dB) + 10nSF log d0 (52) +FAF (dB) + PAF (dB)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 200 / 303
  • 640. Attenuation Factor Model Figure: Scatter plot of path loss as a function of distance in office building 1Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 201 / 303
  • 641. Attenuation Factor Model Figure: Scatter plot of path loss as a function of distance in office building 2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 202 / 303
  • 642. Signal Penetration into Buildings 1 Effect of frequencyCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 203 / 303
  • 643. Signal Penetration into Buildings 1 Effect of frequency Penetration losses with increase in frequencyCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 203 / 303
  • 644. Signal Penetration into Buildings 1 Effect of frequency Penetration losses with increase in frequency 2 Effect of Height Frequency (MHz) Loss(dB) 44.1 16.4 896.5 111.6 1400 7.6Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 203 / 303
  • 645. Signal Penetration into Buildings 1 Effect of frequency Penetration losses with increase in frequency 2 Effect of Height Penetration loss decreases with the height of the building upto some certain height Frequency (MHz) Loss(dB) 44.1 16.4 896.5 111.6 1400 7.6Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 203 / 303
  • 646. Signal Penetration into Buildings 1 Effect of frequency Penetration losses with increase in frequency 2 Effect of Height Penetration loss decreases with the height of the building upto some certain height At lower heights, the urban clutter induces greater attenuation and then it increases Frequency (MHz) Loss(dB) 44.1 16.4 896.5 111.6 1400 7.6Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 203 / 303
  • 647. Signal Penetration into Buildings 1 Effect of frequency Penetration losses with increase in frequency 2 Effect of Height Penetration loss decreases with the height of the building upto some certain height At lower heights, the urban clutter induces greater attenuation and then it increases Shadowing effects of adjacent buildings Frequency (MHz) Loss(dB) 44.1 16.4 896.5 111.6 1400 7.6Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 203 / 303
  • 648. Multipath and Fading 1 The wireless channel is a multipath propagation channelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 204 / 303
  • 649. Multipath and Fading 1 The wireless channel is a multipath propagation channel 2 Multipath in the radio channel causes rapid fluctuation of signal amplitude, called small scale fading or simply fadingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 204 / 303
  • 650. Multipath and Fading 1 The wireless channel is a multipath propagation channel 2 Multipath in the radio channel causes rapid fluctuation of signal amplitude, called small scale fading or simply fading 3 Fading is caused by destructive interference of two or more versions of the transmitted signal arriving at the receiver at slightly different times with different amplitude and phases.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 204 / 303
  • 651. Multipath and FadingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 205 / 303
  • 652. Multipath and FadingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 206 / 303
  • 653. Multipath and Fading 1 Delayed signals are the result of reflections or scatterings from terrain features such as trees, hills or mountains or objects such as people, vehicles or buildingsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 207 / 303
  • 654. Multipath and Fading 1 Delayed signals are the result of reflections or scatterings from terrain features such as trees, hills or mountains or objects such as people, vehicles or buildings 2 The received may vary in amplitude and phase over a short period of time or travel distanceCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 207 / 303
  • 655. Multipath and Fading 1 Delayed signals are the result of reflections or scatterings from terrain features such as trees, hills or mountains or objects such as people, vehicles or buildings 2 The received may vary in amplitude and phase over a short period of time or travel distance 3 The receiver may be stationary or mobileCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 207 / 303
  • 656. Multipath and Fading 1 At the receiver the radio waves generated from the same transmitted signal may comeCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 208 / 303
  • 657. Multipath and Fading 1 At the receiver the radio waves generated from the same transmitted signal may come Different directionsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 208 / 303
  • 658. Multipath and Fading 1 At the receiver the radio waves generated from the same transmitted signal may come Different directions with different propagation delaysCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 208 / 303
  • 659. Multipath and Fading 1 At the receiver the radio waves generated from the same transmitted signal may come Different directions with different propagation delays with different amplitudesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 208 / 303
  • 660. Multipath and Fading 1 At the receiver the radio waves generated from the same transmitted signal may come Different directions with different propagation delays with different amplitudes with different phasesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 208 / 303
  • 661. Multipath and Fading 1 At the receiver the radio waves generated from the same transmitted signal may come Different directions with different propagation delays with different amplitudes with different phases with different angles of arrivalCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 208 / 303
  • 662. Multipath and Fading 1 At the receiver the radio waves generated from the same transmitted signal may come Different directions with different propagation delays with different amplitudes with different phases with different angles of arrival 2 These multipath components combine vectorially at the receiver antenna and cause the total signalCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 208 / 303
  • 663. Multipath and Fading 1 At the receiver the radio waves generated from the same transmitted signal may come Different directions with different propagation delays with different amplitudes with different phases with different angles of arrival 2 These multipath components combine vectorially at the receiver antenna and cause the total signal to fadeCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 208 / 303
  • 664. Multipath and Fading 1 At the receiver the radio waves generated from the same transmitted signal may come Different directions with different propagation delays with different amplitudes with different phases with different angles of arrival 2 These multipath components combine vectorially at the receiver antenna and cause the total signal to fade to distortCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 208 / 303
  • 665. Effects of Multipath and Fading 1 Fading/Multipath results inCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 209 / 303
  • 666. Effects of Multipath and Fading 1 Fading/Multipath results in Rapid changes in signal strength over small travel distances or short time intervalsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 209 / 303
  • 667. Effects of Multipath and Fading 1 Fading/Multipath results in Rapid changes in signal strength over small travel distances or short time intervals Random frequency modulation due to varying Doppler shifts on different multipath signalsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 209 / 303
  • 668. Effects of Multipath and Fading 1 Fading/Multipath results in Rapid changes in signal strength over small travel distances or short time intervals Random frequency modulation due to varying Doppler shifts on different multipath signals Time dispersion due to multipath propagation delaysCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 209 / 303
  • 669. Mobility with respect to Fading 1 When the receiver is mobileCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 210 / 303
  • 670. Mobility with respect to Fading 1 When the receiver is mobile Other objects may be mobile or stationaryCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 210 / 303
  • 671. Mobility with respect to Fading 1 When the receiver is mobile Other objects may be mobile or stationary 2 If other objects are stationaryCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 210 / 303
  • 672. Mobility with respect to Fading 1 When the receiver is mobile Other objects may be mobile or stationary 2 If other objects are stationary Motion is only due to mobile receiverCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 210 / 303
  • 673. Mobility with respect to Fading 1 When the receiver is mobile Other objects may be mobile or stationary 2 If other objects are stationary Motion is only due to mobile receiver Fading is purely a spatial phenomenon (happens only when the mobile receiver moves)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 210 / 303
  • 674. Mobility with respect to Fading 1 When the receiver is mobile Other objects may be mobile or stationary 2 If other objects are stationary Motion is only due to mobile receiver Fading is purely a spatial phenomenon (happens only when the mobile receiver moves) The spatial variations as the mobile moves will be perceived as temporal variations.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 210 / 303
  • 675. Factors Influencing Small-Scale Fading 1 Multipath PropagationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 211 / 303
  • 676. Factors Influencing Small-Scale Fading 1 Multipath Propagation Presence of reflecting objects and scatters causesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 211 / 303
  • 677. Factors Influencing Small-Scale Fading 1 Multipath Propagation Presence of reflecting objects and scatters causes 1 Multiple versions of the signal to arrive at the receiver with different amplitude ans time delaysCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 211 / 303
  • 678. Factors Influencing Small-Scale Fading 1 Multipath Propagation Presence of reflecting objects and scatters causes 1 Multiple versions of the signal to arrive at the receiver with different amplitude ans time delays 2 The total signal at receiver to fade or distortCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 211 / 303
  • 679. Factors Influencing Small-Scale Fading 1 Multipath Propagation Presence of reflecting objects and scatters causes 1 Multiple versions of the signal to arrive at the receiver with different amplitude ans time delays 2 The total signal at receiver to fade or distort 2 Speed of mobileCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 211 / 303
  • 680. Factors Influencing Small-Scale Fading 1 Multipath Propagation Presence of reflecting objects and scatters causes 1 Multiple versions of the signal to arrive at the receiver with different amplitude ans time delays 2 The total signal at receiver to fade or distort 2 Speed of mobile Causes Doppler shift at each multipath componentCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 211 / 303
  • 681. Factors Influencing Small-Scale Fading 1 Multipath Propagation Presence of reflecting objects and scatters causes 1 Multiple versions of the signal to arrive at the receiver with different amplitude ans time delays 2 The total signal at receiver to fade or distort 2 Speed of mobile Causes Doppler shift at each multipath component Causes random frequency modulationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 211 / 303
  • 682. Factors Influencing Small-Scale Fading 1 Multipath Propagation Presence of reflecting objects and scatters causes 1 Multiple versions of the signal to arrive at the receiver with different amplitude ans time delays 2 The total signal at receiver to fade or distort 2 Speed of mobile Causes Doppler shift at each multipath component Causes random frequency modulation Doppler shift will be positive or negative depending on whether the mobile is moving toward or away from the BSCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 211 / 303
  • 683. Factors Influencing Small-Scale Fading Speed of surrounding objectsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 212 / 303
  • 684. Factors Influencing Small-Scale Fading Speed of surrounding objects 1 Causes time-varying Doppler shift on the multipath componentsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 212 / 303
  • 685. Factors Influencing Small-Scale Fading Speed of surrounding objects 1 Causes time-varying Doppler shift on the multipath components 2 If the surrounding objects move at a greater rate than the mobile, this effects dominates the small scale fadingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 212 / 303
  • 686. Factors Influencing Small-Scale Fading Speed of surrounding objects 1 Causes time-varying Doppler shift on the multipath components 2 If the surrounding objects move at a greater rate than the mobile, this effects dominates the small scale fading 3 If the surrounding objects move at a smaller rate than the mobile their effect can be ignoredCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 212 / 303
  • 687. Factors Influencing Small-Scale Fading Speed of surrounding objects 1 Causes time-varying Doppler shift on the multipath components 2 If the surrounding objects move at a greater rate than the mobile, this effects dominates the small scale fading 3 If the surrounding objects move at a smaller rate than the mobile their effect can be ignored 4 The term Coherence time determines how static the channel is (and depends on the Doppler shift)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 212 / 303
  • 688. Factors Influencing Small-Scale Fading The transmission bandwidth of the signalCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 213 / 303
  • 689. Factors Influencing Small-Scale Fading The transmission bandwidth of the signal 1 The transmitted radio signal bandwidth and bandwidth of the multiple channel decideCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 213 / 303
  • 690. Factors Influencing Small-Scale Fading The transmission bandwidth of the signal 1 The transmitted radio signal bandwidth and bandwidth of the multiple channel decide To what extent does the amplitude fluctuateCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 213 / 303
  • 691. Factors Influencing Small-Scale Fading The transmission bandwidth of the signal 1 The transmitted radio signal bandwidth and bandwidth of the multiple channel decide To what extent does the amplitude fluctuate To what extent the signal distortCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 213 / 303
  • 692. Factors Influencing Small-Scale Fading The transmission bandwidth of the signal 1 The transmitted radio signal bandwidth and bandwidth of the multiple channel decide To what extent does the amplitude fluctuate To what extent the signal distort 2 The channel bandwidth can be quantified by the term called Coherence BandwidthCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 213 / 303
  • 693. Factors Influencing Small-Scale Fading The transmission bandwidth of the signal 1 The transmitted radio signal bandwidth and bandwidth of the multiple channel decide To what extent does the amplitude fluctuate To what extent the signal distort 2 The channel bandwidth can be quantified by the term called Coherence Bandwidth 3 The term Coherence bandwidth is a measure of the maximum frequency difference for which the signals are still strongly correlated in amplitudeCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 213 / 303
  • 694. Terminologies Level Crossing RateCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 214 / 303
  • 695. Terminologies Level Crossing Rate 1 Average number of times per second that the signal envelope crosses the level in positive going directionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 214 / 303
  • 696. Terminologies Level Crossing Rate 1 Average number of times per second that the signal envelope crosses the level in positive going direction Fading RateCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 214 / 303
  • 697. Terminologies Level Crossing Rate 1 Average number of times per second that the signal envelope crosses the level in positive going direction Fading Rate 1 Number of times signal envelope crosses middle value in positive going direction per unit timeCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 214 / 303
  • 698. Terminologies Level Crossing Rate 1 Average number of times per second that the signal envelope crosses the level in positive going direction Fading Rate 1 Number of times signal envelope crosses middle value in positive going direction per unit time Depth of FadingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 214 / 303
  • 699. Terminologies Level Crossing Rate 1 Average number of times per second that the signal envelope crosses the level in positive going direction Fading Rate 1 Number of times signal envelope crosses middle value in positive going direction per unit time Depth of Fading 1 Ratio of mean square value and minimum value of fading signalCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 214 / 303
  • 700. Terminologies Level Crossing Rate 1 Average number of times per second that the signal envelope crosses the level in positive going direction Fading Rate 1 Number of times signal envelope crosses middle value in positive going direction per unit time Depth of Fading 1 Ratio of mean square value and minimum value of fading signal Fading DurationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 214 / 303
  • 701. Terminologies Level Crossing Rate 1 Average number of times per second that the signal envelope crosses the level in positive going direction Fading Rate 1 Number of times signal envelope crosses middle value in positive going direction per unit time Depth of Fading 1 Ratio of mean square value and minimum value of fading signal Fading Duration 1 Time for which signal is below given thresholdCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 214 / 303
  • 702. Doppler Effect When a wave source (transmitter) and/or a receiver is/are moving, the frequency of the received signal will not be the same as that of the transmitted signalCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 215 / 303
  • 703. Doppler Effect When a wave source (transmitter) and/or a receiver is/are moving, the frequency of the received signal will not be the same as that of the transmitted signal 1 When they are moving toward each other, the frequency of the received signal is higher than the sourceCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 215 / 303
  • 704. Doppler Effect When a wave source (transmitter) and/or a receiver is/are moving, the frequency of the received signal will not be the same as that of the transmitted signal 1 When they are moving toward each other, the frequency of the received signal is higher than the source 2 When they are opposing each other, the frequency decreasesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 215 / 303
  • 705. Doppler Effect When a wave source (transmitter) and/or a receiver is/are moving, the frequency of the received signal will not be the same as that of the transmitted signal 1 When they are moving toward each other, the frequency of the received signal is higher than the source 2 When they are opposing each other, the frequency decreases Thus, the frequency of the received signal is fR = fc − fD where fc is the frequency of source carrier fD is the Doppler shift in frequencyCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 215 / 303
  • 706. Doppler Effect Assume mobile transmitter and stationary receiverCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 216 / 303
  • 707. Doppler Effect v fD = cos θ where v is the moving speed λ λ is the wavelength of carrierCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 217 / 303
  • 708. Doppler Effect v fD = cos θ where v is the moving speed λ λ is the wavelength of carrier Clearly, Doppler shift (fD ) depends onCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 217 / 303
  • 709. Doppler Effect v fD = cos θ where v is the moving speed λ λ is the wavelength of carrier Clearly, Doppler shift (fD ) depends on 1 The relative velocity of the receiver with respect to transmitterCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 217 / 303
  • 710. Doppler Effect v fD = cos θ where v is the moving speed λ λ is the wavelength of carrier Clearly, Doppler shift (fD ) depends on 1 The relative velocity of the receiver with respect to transmitter 2 The frequency (or wavelength) of transmissionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 217 / 303
  • 711. Doppler Effect v fD = cos θ where v is the moving speed λ λ is the wavelength of carrier Clearly, Doppler shift (fD ) depends on 1 The relative velocity of the receiver with respect to transmitter 2 The frequency (or wavelength) of transmission 3 The direction of travelling with respect to the direction of the arriving signalCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 217 / 303
  • 712. Doppler ShiftCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 218 / 303
  • 713. Doppler Shift d =| XY |Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 219 / 303
  • 714. Doppler Shift d =| XY | ∆I =| SX | − | SY |= d cos θCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 219 / 303
  • 715. Doppler Shift d =| XY | ∆I =| SX | − | SY |= d cos θ ∆I = ν∆t cos θCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 219 / 303
  • 716. Doppler Shift d =| XY | ∆I =| SX | − | SY |= d cos θ ∆I = ν∆t cos θ The phase change in the received signal is 2π∆l 2πν∆t ∆φ = = cos θ λ λCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 219 / 303
  • 717. Doppler Shift d =| XY | ∆I =| SX | − | SY |= d cos θ ∆I = ν∆t cos θ The phase change in the received signal is 2π∆l 2πν∆t ∆φ = = cos θ λ λ 1 ∆φ v Doppler Shift : fd = . = . cos θ 2π ∆t λCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 219 / 303
  • 718. Doppler Shift The Doppler shift is positiveCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 220 / 303
  • 719. Doppler Shift The Doppler shift is positive 1 If the mobile is moving toward the direction of arrival of the waveCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 220 / 303
  • 720. Doppler Shift The Doppler shift is positive 1 If the mobile is moving toward the direction of arrival of the wave The Doppler shift is negativeCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 220 / 303
  • 721. Doppler Shift The Doppler shift is positive 1 If the mobile is moving toward the direction of arrival of the wave The Doppler shift is negative 1 If the mobile is moving away from the direction of arrival of the waveCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 220 / 303
  • 722. Delay Spread Each multipath signal travels different path length, so the time of arrival for each path is differentCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 221 / 303
  • 723. Delay Spread Each multipath signal travels different path length, so the time of arrival for each path is different A single transmitted pulse will be spread in time when it reaches the receiver. This effect which spreads out the signal is called Delay SpreadCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 221 / 303
  • 724. Delay Spread Each multipath signal travels different path length, so the time of arrival for each path is different A single transmitted pulse will be spread in time when it reaches the receiver. This effect which spreads out the signal is called Delay Spread Delay spread leads to increase in the signal bandwidthCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 221 / 303
  • 725. Delay Spread Each multipath signal travels different path length, so the time of arrival for each path is different A single transmitted pulse will be spread in time when it reaches the receiver. This effect which spreads out the signal is called Delay Spread Delay spread leads to increase in the signal bandwidth Delay spread is the property of the communication channelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 221 / 303
  • 726. Doppler ShiftCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 222 / 303
  • 727. Inter Symbol Interference If Delay Spread of the channel is comparable with the symbol length, we get ISICellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 223 / 303
  • 728. Inter Symbol Interference If Delay Spread of the channel is comparable with the symbol length, we get ISI 1 Second multipath is delayed and is received during next symbolCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 223 / 303
  • 729. Inter Symbol Interference If Delay Spread of the channel is comparable with the symbol length, we get ISI 1 Second multipath is delayed and is received during next symbol ISI has impact on burst error rate of channelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 223 / 303
  • 730. Inter Symbol Interference If Delay Spread of the channel is comparable with the symbol length, we get ISI 1 Second multipath is delayed and is received during next symbol ISI has impact on burst error rate of channel 1 For low bit-error rate (BER)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 223 / 303
  • 731. Inter Symbol Interference If Delay Spread of the channel is comparable with the symbol length, we get ISI 1 Second multipath is delayed and is received during next symbol ISI has impact on burst error rate of channel 1 For low bit-error rate (BER) 1 2 R¡ τdCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 223 / 303
  • 732. Inter Symbol Interference If Delay Spread of the channel is comparable with the symbol length, we get ISI 1 Second multipath is delayed and is received during next symbol ISI has impact on burst error rate of channel 1 For low bit-error rate (BER) 1 2 R¡ τd 3 R (digital transmission rate) is limited by delay spreadCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 223 / 303
  • 733. Doppler ShiftCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 224 / 303
  • 734. Impulse Response of a Multipath Channel The small-scale variations of a mobile radio signal can be directly related to the impulse response of mobile radio channelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 225 / 303
  • 735. Impulse Response of a Multipath Channel The small-scale variations of a mobile radio signal can be directly related to the impulse response of mobile radio channel The impulse response is a wideband channel characterizationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 225 / 303
  • 736. Impulse Response of a Multipath Channel The small-scale variations of a mobile radio signal can be directly related to the impulse response of mobile radio channel The impulse response is a wideband channel characterization It contains all the information necessary toCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 225 / 303
  • 737. Impulse Response of a Multipath Channel The small-scale variations of a mobile radio signal can be directly related to the impulse response of mobile radio channel The impulse response is a wideband channel characterization It contains all the information necessary to 1 Simulate the channelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 225 / 303
  • 738. Impulse Response of a Multipath Channel The small-scale variations of a mobile radio signal can be directly related to the impulse response of mobile radio channel The impulse response is a wideband channel characterization It contains all the information necessary to 1 Simulate the channel 2 Analyse the channelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 225 / 303
  • 739. Impulse Response of a Multipath Channel The small-scale variations of a mobile radio signal can be directly related to the impulse response of mobile radio channel The impulse response is a wideband channel characterization It contains all the information necessary to 1 Simulate the channel 2 Analyse the channel This is because the mobile radio channel can be modelled as a linear filter with a time varying impulse responseCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 225 / 303
  • 740. Impulse Response of a Multipath Channel Multipath fading is characterized by the channel impulse response, which includes the information ofCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 226 / 303
  • 741. Impulse Response of a Multipath Channel Multipath fading is characterized by the channel impulse response, which includes the information of 1 relative timeCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 226 / 303
  • 742. Impulse Response of a Multipath Channel Multipath fading is characterized by the channel impulse response, which includes the information of 1 relative time 2 signal power andCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 226 / 303
  • 743. Impulse Response of a Multipath Channel Multipath fading is characterized by the channel impulse response, which includes the information of 1 relative time 2 signal power and 3 signal phase when the delayed signals arrive at the receiver, as compared to the direct waveCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 226 / 303
  • 744. Impulse Response of a Multipath Channel Multipath fading is characterized by the channel impulse response, which includes the information of 1 relative time 2 signal power and 3 signal phase when the delayed signals arrive at the receiver, as compared to the direct wave 4 If there is a mobile reception, then the relative lengths and attenuations of the various reception paths will change with time, that is the channel is time varyingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 226 / 303
  • 745. Impulse Response of a Multipath Channel Multipath fading is characterized by the channel impulse response, which includes the information of 1 relative time 2 signal power and 3 signal phase when the delayed signals arrive at the receiver, as compared to the direct wave 4 If there is a mobile reception, then the relative lengths and attenuations of the various reception paths will change with time, that is the channel is time varying 5 We assume that time variation are strictly due to the receiver motion (t=d/v)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 226 / 303
  • 746. Impulse Response of a Multipath Channel When we observe a multipath-fading environment from the perspective of frequency domain, a characteristic of multipath fading is that some frequencies are enhanced whereas others are attenuatedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 227 / 303
  • 747. Impulse Response of a Multipath Channel Since at any distance d=vt, the received power will have combination of different incoming signals, having different propagation delays, depending on the distance d between the transmitter and receiverCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 228 / 303
  • 748. Impulse Response of a Multipath Channel Since at any distance d=vt, the received power will have combination of different incoming signals, having different propagation delays, depending on the distance d between the transmitter and receiver Hence the channel characteristics, or the impulse response function depends on d, the separation between transmitter and receiverCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 228 / 303
  • 749. Impulse Response of a Multipath Channel Figure: The mobile radio channel as a function of time and space Consider a receiver moving along the ground at some constant velocity v Let x(t) represents the transmitted signal y d(t) represents the received signal at position d h(d,t) represents the channel impulse response which is dependent on d (hence time-varying d=vt)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 229 / 303
  • 750. Impulse Response of a Multipath Channel Figure: Multipath ChannelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 230 / 303
  • 751. Impulse Response Model of a Multipath Channel ∞ y (d, t) = x(t) ⊗ h(d, t) = x(τ )h(d, t − τ )dτ −∞ For a casual system h(d, t) = 0 for t < 0; hence the equation t reduces to y (d, t) = x(τ )h(d, t − τ )dτ −∞Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 231 / 303
  • 752. Impulse Response of a Multipath Channel ∞ y (d, t) = x(t) ⊗ h(d, t) = x(τ )h(d, t − τ )dτ −∞ For a casual system h(d, t) = 0 for t < 0; hence the equation t reduces to y (d, t) = x(τ )h(d, t − τ )dτ −∞Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 232 / 303
  • 753. Impulse Response Model of a Multipath Channel Since the receiver moves along the ground at a constant velocity v, the position of the receiver can be expressed as d = vt t y (vt, t) = x(τ )h(vt, t − τ )dτ (53) −∞ t y (t) = x(τ )h(vt, t − τ )dτ = x(t) ⊗ h(vt, t) = x(t) ⊗ h(d, t) −∞ (54) where x(t) is the transmitted signal y(t) is the received signal h(t,τ ) = Impulse response of the channel τ Multipath delay of the channel for a fixed value of tCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 233 / 303
  • 754. Impulse Response Model of a Multipath Channel y (t) = x(τ )h(t, τ )dτ = x(t)h(t, τ ) (55) The impulse response is a function of both t and τ t represents the variations due to motion τ represents the channel multipath delay for a fixed value of tCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 234 / 303
  • 755. Impulse Response Model of a Multipath Channel x(t) ⇒ h(t, τ ) = Re hb (t, τ )e jωc t ⇒ y (t) (56) y (t) = Re r (t)e jωc t y (t) = x(t) ⊗ h(t) 1 c(t) ⇒ hb (t, τ ) ⇒ r (t) (57) 2 1 r (t) = c(t) ⊗ hb (t) 2 Equation (4) represents the Bandpass Impulse Response Model Equation (5) represents the Baseband equivalent channel impulse response modelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 235 / 303
  • 756. Impulse Response Model of a Multipath Channel 1 r (t) = c(t) ⊗ hb (t, τ ) (58) 2 x(t) = Re [c(t)exp(j2πfc t)] y (t) = Re [r (t)exp(j2πfc t)] c(t) represents the complex envelope of the transmitted signal r(t) represents the complex envelope of the received signal h(t, τ ) represents the complex baseband impulse responseCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 236 / 303
  • 757. Impulse Response Model of a Multipath Channel Let x(t) represents a baseband signal. Then x(t) = Re [c(t)exp(j2πfc t)] = c(t) cos(2πfc t) 2 Pavg = 0.5| c(t) |Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 237 / 303
  • 758. Model of Multipath Channel Discretize the multipath delay axis τ into equal time delay segments called Excess Delay bins If there are N such multipath components (0,N-1)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 238 / 303
  • 759. Discrete-time Impulse Response Model of Multipath ChannelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 239 / 303
  • 760. Discrete-time Impulse Response Model of Multipath Channel Two components emerging from the same source at the same time, but arriving at the same receiver after travelling different paths withCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 240 / 303
  • 761. Discrete-Time Impulse Response Model for a Multipath Channel If the channel impulse response is assumed to be time-invariant over small scale time or distance interval, then it may be simplified as N−1 hb (τ ) = ai exp(jθi )δ(τ − τi ) (59) i=0 When measuring or predicting hb (t), a probing pulse p(t) which approximates the unit impulse function is used at the transmitter. That is p(t) = δ(t − τ ) (60)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 241 / 303
  • 762. Power Delay Profile For small-scale fading, the power delay profile of the channel is found by taking the spatial average of | hb (t, τ ) | over a small area If p(t) has a time duration much smaller than the impulse response of the multipath channel, the receive power delay profile in a local area is given by P(τ ) = k| hb (t; τ ) |2 (61) where the bar represents the average over the local area and several snapshots of | hb (t; τ ) |2 Gain k relates the transmitter power in the probing pulse p(t) tot he total received power in a multipath delay profileCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 242 / 303
  • 763. Bandwidth and Received Power The impulse response of a multipath channel is measured in the field using channel sounding techniques The small scale fading behaves differently for two signals with different bandwidths Two extreme channel sounding techniques are : 1 Using a wideband probing signal (a narrow pulse) 2 Using a continuous wave (a narrowband signal)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 243 / 303
  • 764. Case 1: Narrow Pulse (wideband signal) x(t) ⇒ Multipath Wireless Channel ⇒ r(t) TREP ≥ τmax x(t) = Re{p(t)e j2πfc t } = p(t) cos (2πfc t) τmax p(t) = 2 for 0 ≤ t ≤ Tbb TbbCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 244 / 303
  • 765. Case 1: Wideband signals The output r(t) will approximate the channel impulse response since p(t) approximates unit impulses Th lowpass channel output r(t) is found by convolving p(t) with hb (t, τ ) N−1 1 r(t) = ai e jθi .p(t − τi ) 2 i=0 N−1 τmax Tbb r(t) = ai e jθi . rect t − − τi i=0 Tbb 2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 245 / 303
  • 766. Receive Power of Wideband signals To determine the receive power at a time t0 , the power | r (t0 ) |2 The quantity | r (t0 ) |2 is found by summing up the multipath powers resolved in the instantaneous multipath power delay profile | hb (t0 ; τ ) |2Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 246 / 303
  • 767. Receive Power of Wideband signals 1 ∞ | r (t0 ) |2 = −∞ r (t) × r (t)dt = τmax N−1 N−1 1 τmax 1 0 Re aj (t0 )ai (t0 )p(t − τ j)p(t − τ i)exp (j(θj − θi )) τmax 4 j=0 j=0 If all the multipath components are resolved by the probe p(t), then | τj − τi |> Tbb for all j = i and N−1 1 τmax 1 | r (t0 ) |2 = a2 (t0 )p 2 (t − τk ) dt τmax 0 4 k=0 k N−1 τmax 2 1 2 τmax Tbb = ak (t0 ) rect t − − τk dt τmax k=0 0 Tbb 2 N−1 2 = ak (t0 ) k=0Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 247 / 303
  • 768. Receive Power of Wideband signals Assume that received power forms a random process, where each multipath component has a random amplitude and phase time at t The average small-scale received power for wideband probe is given by N−1 N−1 2 Ea.θ [PWB ] = Ea.θ | ai exp(jθi ) | = ai 2 (62) i=0 i=0 This shows that if all the multipath components of a transmitted signal are resolved at the receiver then the average small received power is the sum of the received powers in each multipath componentCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 248 / 303
  • 769. Receive Power of Wideband signals In practice the amplitudes of individual multipath components do not fluctuate widely in a local area (for distance in the order of the wavelength or a fraction of the wavelength) This means the average received power of a wideband signal do not fluctuate significantly when the receiver is moved about in a local areaCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 249 / 303
  • 770. Case 2: CW signal (Narrowband Signal) Consider a CW signal is transmitted into the same multipath channel Let the complex envelope be given by c(t) =2 Then the instantaneous envelope of the constant signal is given by N−1 r (t) = ai e (jθi (t,τ )) (63) i=0Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 250 / 303
  • 771. Case 2: CW signal (Narrowband Signal) The instantaneous power is given by N−1 | r (t) |2 =| ai e (jθi (t,τ )) |2 (64) i=0 ai varies little over local areas, but θi may change a lot As a result, for CW (narrowband) signals, small movements may cause large fluctuations on the instantaneous received power, which typifies small-scale fading for CW signals.Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 251 / 303
  • 772. Average received power of Narrowband Signals over a local area N−1 Ea,θ [PCW ] = Ea,θ | ai e (jθi (t,τ )) |2 i=0 N−1 N−1 N (65) = ai 2 + 2 rij cos(θi − θj ) i=0 i=0 i,j=i where rij is the path amplitude correlation coefficient defined to be rij = Ea [ai aj ]Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 252 / 303
  • 773. Received power of Wideband and Narrowband Signals When cos(θi − θj ) = 0 and/or rij = 0 then the average received power for a CW signal over a small-scale region is equivalent to the average received power for a wideband signal This may occur when 1 The phases of multipath component at different locations over the small-scale region are i.i.d uniform distributed over [0, 2π]Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 253 / 303
  • 774. Small Scale Multipath Measurements Multipath structure is important for determining small-scale fading A number of channel sounding techniques have been developedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 254 / 303
  • 775. Channel Sounding Techniques Direct RF Pulse Spectrum Spread Spectrum Sliding Correlator Channel Sounding Frequency domain channel soundingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 255 / 303
  • 776. Direct RF Channel Measurement A direct RF pulse system is used This helps us to find the power delay profile directly A narrow pulse is used for channel sounding At the receiver, the signal is amplified and detected using an envelope detector It is then stored on a high speed digital storage oscilloscope If the receiver is set on the averaging mode, local average power delay profile is obtainedCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 256 / 303
  • 777. Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 257 / 303
  • 778. Direct RF Channel Measurement 1 Problems Subject to interference Subject to noise due to wide passband filter required for multipath time resolution The pulse system relies on the ability to trigger the oscilloscope on the fast arriving pulse The phases of the individual multipath components are not received because of the use of the envelope detectorCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 258 / 303
  • 779. Spread Spectrum Channel Impulse Response Measurement System The probing signal is wideband but the receiver is narrowband, preceded by a wideband mixer Thus the dynamic range of the receiver is much larger than the RF pulse measurement system The carrier signal is spread over a large bandwidth by mixing it with a binary pseudo-noise (PN) sequence having a chip duration Tc At the receiver, the signal is filtered and despread using the same PN sequence The transmitter chip clock is run at a slightly faster rate than receiver chip clock This results in a sliding correlatorCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 259 / 303
  • 780. Spread Spectrum Channel Impulse Response Measurement System When the chip sequence of the faster clock rate catches up with the slower one, the sequences will be maximally correlated When the sequences are not maximally correlated, mixing will further spread the signal In this case the narrow band filter, that follows the correlator rejects almost all the incoming signalCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 260 / 303
  • 781. Spread Spectrum Channel Impulse Response Measurement SystemCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 261 / 303
  • 782. Spread Spectrum Channel Impulse Response Measurement System 1 The chip rate = Rc = Tc RF bandwidth = 2Rc Tbb Processing Gain = 2 Tc 2 The time resolution = ∆τ = Rc α The slide factor γ = where α = transmitter chip clock (α − β) rate β = receiver chip clock rateCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 262 / 303
  • 783. Spread Spectrum Channel Impulse Response Measurement System 1 Advantages Ability to reject passband noise Improves the coverage range for a given transmitter power Transmitter - Receiver synchronization problem is eliminated using a sliding correlator Sensitivity is adjustable by tweaking the sliding factor and post correlator filter bandwidth Required power is much lower because of the processing gainCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 263 / 303
  • 784. Spread Spectrum Channel Impulse Response Measurement System 1 Disadvantages Measurements are not made real-time (they are made and stored as PN sequences slide past each other) The associated time required is more Since a non-coherent detector is used, the phase information is lostCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 264 / 303
  • 785. Frequency Domain Channel Impulse Response Measurement System Because of the dual relationship between time and frequency, it is possible to measure the channel impulse response in frequency domain A vector network analyser is typically used An S-parameter test set is used to monitor the frequency response of the channel The frequency sweeper scans a particular frequency band by stepping through discrete frequenciesCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 265 / 303
  • 786. Frequency Domain Channel Impulse Response Measurement SystemCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 266 / 303
  • 787. Frequency Domain Channel Impulse Response Measurement System The number and spacing of the frequency steps impact the time resolution of the impulse response measurements The network analyzer determines the complex response S21 (ω) of the channel over the measured frequency range This transmissivity response is a frequency domain representation of the channel impulse response This response is converted into time domain by Inverse Discrete Fourier Transform (IDFT)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 267 / 303
  • 788. Frequency Domain Channel Impulse Response Measurement System 1 Disadvantages System requires careful calibration System requires hard-wired synchronization between the transmitter and receiver Practical only for indoor channel measurements Non real-time nature of measurement For time varying channels the channel impulse response may change giving enormous measurementsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 268 / 303
  • 789. Frequency Domain Channel Impulse Response Measurement System 1 Solution Use fast sweep time in order to keep the frequency response measurement interval as short as possible Faster sweep times comes at the cost of fewer frequency steps This leads to poorer time resolutionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 269 / 303
  • 790. Parameters of Mobile Multipath Channels Derived from the power delay profile Power delay can be measured in Time Domain Frequency Domain Important parameters are Time Dispersion Parameters Coherence Bandwidth Doppler Spread and coherence timeCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 270 / 303
  • 791. Power Delay Profile Measured by Channel sounding techniques Plots of relative received power as a function of excess delay, with respect to a fixed time delay reference Found by averaging instantaneous power delay measurements over a local area λ Sampling interval is approximately 4 For local area it is less than 6m outdoors and less than 2m in indoorsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 271 / 303
  • 792. Outdoor Power Delay ProfileCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 272 / 303
  • 793. Indoor Power Delay ProfileCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 273 / 303
  • 794. Time Dispersion Parameters Grossly quantify the multipath channel Parameters include Mean Excess Delay RMS Delay Spread Maximum Excess Delay (X dB)Cellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 274 / 303
  • 795. Time Dispersion Parameters Mean Excess Delay τ is the first moment of the power delay profile and is given by 2 ak τk p(τk )τk k k τ= = (66) 2 ak p(τk ) k kCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 275 / 303
  • 796. Time Dispersion Parameters RMS Delay Spread (στ ) Each multipath signal travels different path length, so the time of arrival for each path length is different A single transmitted pulse will be spread in time when it reaches the receiver. This effect which spreads out the signal is call Delay Spread Delay spread leads to increase in bandwidthCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 276 / 303
  • 797. Time Dispersion Parameters RMS Delay Spread (στ ) Characterizes the time-dispersiveness of the channel Obtained from power delay profile Indicates delay during which the power of the received signal is above a certain threshold It is the square root of the second central movement of the power delay profile στ = τ 2 − (τ )2 2 2 2 ak τk p(τk )τk (67) k k τ2 = = 2 ak p(τk ) k kCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 277 / 303
  • 798. Measured values of RMS Delay SpreadCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 278 / 303
  • 799. Time Dispersion Parameters Maximum Excess Delay (X Db)) Time delay during which multipath energy falls to X dB below the maximum M.E.D (X dB) = τx − τ0 where τ0 is the first arriving signal and τx is the maximum delay at which a multipath component is with in X dB of the strongest arriving multipath signal (which does not arrive necessarily arrive at τ0 ) Defines the temporal extent of the multipath, that is above a particular threshold tx is called the Excess Delay Spread of a power delay profileCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 279 / 303
  • 800. Time Dispersion ParametersCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 280 / 303
  • 801. Coherence Bandwidth A statistical measure of the range of frequencies over which the channel can be considered flat That is the channel passes all spectral components with equal gain and linear phase Represents correlation between 2 fading signal envelopes at frequencies f1 andf2 It is a function of RMS delay spread Two frequencies that are larger than coherence bandwidth fade independently Concept useful in diversity reception Multiple copies of the same message are sent using different frequencies These frequencies are separated by more than the coherence bandwidth of the channel Coherence bandwidth indicates frequency selectivity during transmissionCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 281 / 303
  • 802. Doppler Spread and Coherence Time Delay spread and coherence bandwidth describe only the time dispersive nature of the multipath channel in a local area Doppler Spread and Coherence Time describe the time-varying nature of the channel in a small-scale region Caused by the relative motion of the transmitter and receiverCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 282 / 303
  • 803. Doppler Spread BD v fD = cos θ where v is the velocity and λ is the wavelength of λ the carrier Doppler Spread , BD = Maximum Doppler Shift Doppler Shift (fD ) depends on The relative velocity of the receiver with respect to transmitter The frequency (wavelength) of transmission The direction of travelling with respect to the direction of the arriving signal Characterizes frequency-dispersiveness of the channel , or the spreading of transmitted frequency due to different Doppler shifts Obtained from Doppler spectrum Indicates range of frequencies over which the received Doppler spectrum is above a certain valueCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 283 / 303
  • 804. Doppler Spread BD If the baseband signal bandwidth is much greater than BD then effects of Doppler spread are negligible at the receiver This is a slow fading channelCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 284 / 303
  • 805. Coherence Time Coherence time is a statistical measure of the time duration over which the channel impulse response is essentially time-invariant If the symbol period of the baseband signal is greater than the coherence time of the channel, then the channel will change during the transmission of the signal, hence there will be distortion at the receiver Coherence time is defined as 1 TC = (68) fmCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 285 / 303
  • 806. Coherence Time Popular Thumb Rule Definition 9 TC = 2 (69) 16πfm The definition of coherence time implies that two signal s arriving with a time separation greater than TC are affected differently by the channel A large coherence time ⇒ Channel changes slowlyCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 286 / 303
  • 807. Types of Small-Scale Fading Based on multipath time delay spreadingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 287 / 303
  • 808. Flat Fading Occurs due to fluctuations in the gain of the multipath channel which leads to change in amplitude of the received signal with time For example Rayleigh Distribution Occurs when symbol period of the transmitted signal is much larger than the delay spread of the channel Bandwidth of the applied signal is narrow May cause deep fades Increase the transmit power to combat this situationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 288 / 303
  • 809. Flat Fading Channel CharacteristicsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 289 / 303
  • 810. Frequency selective Fading Occurs when the channel multipath delay spread is greater than the symbol period Symbols face time dispersion Channel induces inter-symbol Interference (ISI) Bandwidth of the signal s(t) is wider than the channel impulse response Causes distortion of the received baseband signalsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 290 / 303
  • 811. Frequency Selective Fading Channel characteristicsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 291 / 303
  • 812. Frequency Selective Fading Channel ModelsCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 292 / 303
  • 813. Flat fading vs Frequency selective Fading Common rule of thumb for Flat Fading Flat Fading Ts > 10σt Frequency selective fading Ts < 10σtCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 293 / 303
  • 814. Types of small scale Fading Based on Doppler SpreadCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 294 / 303
  • 815. Fast Fading Occurs due to Doppler Spread The rate of change of channel characteristics is larger than the rate of change of the transmitted signal . As a result the channel changes during a symbol period The channel changes because of the relative motion between the receiver and baseband signalling Coherence time (Tc )of the channel is smaller than the symbol period (Ts ) of the transmitted signalCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 295 / 303
  • 816. Slow Fading Rate of change of the channel characteristics is much smaller than the rate of change of the transmitted signal The channel may be assumed static over one or several reciprocal bandwidth intervals In frequency domain, this means that Doppler Spread of the channel is much smaller than the bandwidth of the baseband signalCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 296 / 303
  • 817. Fast Fading Vs Slow Fading Velocity of the mobile ( or the velocity of the objects in the channel ) and the baseband signalling determines whether a signal undergoes fast fading or slow fadingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 297 / 303
  • 818. Fading ClassificationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 298 / 303
  • 819. Fading ClassificationCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 299 / 303
  • 820. Fading Distributions Statistical characteristics of the variation of the envelope of the received signal vary over time Two most common distributions 1 Rayleigh Fading 2 Ricean FadingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 300 / 303
  • 821. Rayleigh Fading If all the multipath components have approximately the same amplitude (when MS is far away from BS) the envelope of the received signal is Rayleigh Fading No dominant Signal componentCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 301 / 303
  • 822. Rayleigh FadingCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 302 / 303
  • 823. Ricean Fading When there is a dominant stationary (non-fading) signal component present (such as LOS which is usually possible when MS and BS are close to each other), the fading envelope is Ricean The Ricean distribution degenerates to Rayleigh when the dominant component fades awayCellular and Mobile Communication () Chettinad Tech, Karur January 25, 2013 303 / 303