- The document discusses gain compression, intercept points, and blocking in amplifiers.
- Gain compression occurs when the output signal limits due to supply voltage or bias current constraints, dropping the gain by 1 dB at the 1 dB compression point.
- Intercept points like IIP2 and IIP3 are extrapolated points where intermodulation distortion products equal the fundamental signal.
- A strong interfering "blocker" signal can reduce the gain for a weaker desired signal through cubic distortion terms, an effect known as blocking.
Turbo codes provide reliable communication at high data rates by combining concepts from block and convolutional codes. They use two convolutional encoders separated by an interleaver, producing redundant parity bits. During iterative decoding, probabilistic information from the first decoder is used as a priori information for the second decoder, and vice versa, improving the estimates of the transmitted bits at each iteration. Turbo codes achieve performance close to the theoretical channel capacity limit with low error rates. They have applications in deep space communications, mobile wireless systems, and other areas requiring high reliability transmission.
OFDM (Orthogonal Frequency Division Multiplexing) is a digital modulation technique that divides the available spectrum into multiple orthogonal subcarriers. It has become popular for digital communication systems due to its ability to mitigate multi-path interference through the use of a guard interval between symbols. OFDM allows for high bandwidth efficiency by overlapping subcarriers and its implementation has been enabled by advances in DFT and LSI technology.
This document discusses vestigial sideband (VSB) modulation. VSB modulation is a compromise between single sideband (SSB) and double sideband suppressed carrier (DSB-SC) modulation that overcomes some of the drawbacks of SSB. In VSB, one sideband and a vestige of the other sideband are transmitted together, requiring less bandwidth than DSB but more than SSB. VSB modulation is commonly used for television signal transmission to reduce the bandwidth requirement compared to DSB.
The document discusses turbo codes, which are a type of error correction code used in communication systems. Turbo codes work by concatenating two or more simple convolutional codes with an interleaver between them. This structure allows for iterative decoding that can achieve performance close to the theoretical maximum. The key aspects covered are the turbo code concepts, log likelihood algebra used in decoding, the purpose and types of interleaving, and how recursive systematic convolutional codes are used as the component codes of a turbo code.
The document discusses acoustic echo cancellation using an adaptive filter algorithm. It introduces the problem of acoustic echoes in hands-free communication systems where speech from the far end is captured by the near end microphone and sent back, causing discomfort. It then describes the basic setup, explains what causes acoustic echoes, and discusses why acoustic echo is more serious than network echo. It outlines solutions like using physical tools or an acoustic echo canceller algorithm. The acoustic echo canceller works by using an adaptive filter to generate an echo replica from the far end signal to subtract from and cancel the echo picked up by the microphone. The LMS algorithm is commonly used for adaptation due to its simplicity.
Performance Requirement and Lessons Learnt of LTE Terminal_Transmitter Partcriterion123
1. The document discusses transmitter output power specifications for LTE and WCDMA, including maximum output power levels and tolerances.
2. It provides lessons learned from issues with output power, EVM, and other signal quality metrics on various device bands. Common causes included improper gain mode selection, impedance mismatches, and oscillator pulling from strong RF signals.
3. Key recommendations include separating PA and transceiver shielding areas, compensating output power for temperature and frequency variations, avoiding routing near noise sources, and using proper gain/loss configurations.
1. The document discusses various technical aspects of UMTS link budget design such as typical NodeB and UE sensitivity levels, maximum output power, antenna gain, path loss, dBm, TMA functionality, processing gain, Eb/No targets, pole capacity calculations, and types of handovers.
2. Key information provided includes NodeB sensitivity from -124 to -115 dBm, UE sensitivity from -119 to -105 dBm, maximum NodeB output power of 20-40W, UE maximum transmit power of 21dBm, typical antenna gain of 17dBi, maximum path loss of 135-160dB, and TMA gain of 12dB from noise figure reduction.
3. Calcul
Turbo codes are a type of error correcting code that can achieve performance close to the theoretical maximum allowed by Shannon's limit. Turbo codes use an iterative decoding process between two recursive systematic convolutional encoders separated by an interleaver. This iterative decoding allows turbo codes to correct errors very efficiently. Turbo codes are used in applications like deep space communications and mobile phone networks due to their ability to operate reliably at low signal-to-noise ratios.
Turbo codes provide reliable communication at high data rates by combining concepts from block and convolutional codes. They use two convolutional encoders separated by an interleaver, producing redundant parity bits. During iterative decoding, probabilistic information from the first decoder is used as a priori information for the second decoder, and vice versa, improving the estimates of the transmitted bits at each iteration. Turbo codes achieve performance close to the theoretical channel capacity limit with low error rates. They have applications in deep space communications, mobile wireless systems, and other areas requiring high reliability transmission.
OFDM (Orthogonal Frequency Division Multiplexing) is a digital modulation technique that divides the available spectrum into multiple orthogonal subcarriers. It has become popular for digital communication systems due to its ability to mitigate multi-path interference through the use of a guard interval between symbols. OFDM allows for high bandwidth efficiency by overlapping subcarriers and its implementation has been enabled by advances in DFT and LSI technology.
This document discusses vestigial sideband (VSB) modulation. VSB modulation is a compromise between single sideband (SSB) and double sideband suppressed carrier (DSB-SC) modulation that overcomes some of the drawbacks of SSB. In VSB, one sideband and a vestige of the other sideband are transmitted together, requiring less bandwidth than DSB but more than SSB. VSB modulation is commonly used for television signal transmission to reduce the bandwidth requirement compared to DSB.
The document discusses turbo codes, which are a type of error correction code used in communication systems. Turbo codes work by concatenating two or more simple convolutional codes with an interleaver between them. This structure allows for iterative decoding that can achieve performance close to the theoretical maximum. The key aspects covered are the turbo code concepts, log likelihood algebra used in decoding, the purpose and types of interleaving, and how recursive systematic convolutional codes are used as the component codes of a turbo code.
The document discusses acoustic echo cancellation using an adaptive filter algorithm. It introduces the problem of acoustic echoes in hands-free communication systems where speech from the far end is captured by the near end microphone and sent back, causing discomfort. It then describes the basic setup, explains what causes acoustic echoes, and discusses why acoustic echo is more serious than network echo. It outlines solutions like using physical tools or an acoustic echo canceller algorithm. The acoustic echo canceller works by using an adaptive filter to generate an echo replica from the far end signal to subtract from and cancel the echo picked up by the microphone. The LMS algorithm is commonly used for adaptation due to its simplicity.
Performance Requirement and Lessons Learnt of LTE Terminal_Transmitter Partcriterion123
1. The document discusses transmitter output power specifications for LTE and WCDMA, including maximum output power levels and tolerances.
2. It provides lessons learned from issues with output power, EVM, and other signal quality metrics on various device bands. Common causes included improper gain mode selection, impedance mismatches, and oscillator pulling from strong RF signals.
3. Key recommendations include separating PA and transceiver shielding areas, compensating output power for temperature and frequency variations, avoiding routing near noise sources, and using proper gain/loss configurations.
1. The document discusses various technical aspects of UMTS link budget design such as typical NodeB and UE sensitivity levels, maximum output power, antenna gain, path loss, dBm, TMA functionality, processing gain, Eb/No targets, pole capacity calculations, and types of handovers.
2. Key information provided includes NodeB sensitivity from -124 to -115 dBm, UE sensitivity from -119 to -105 dBm, maximum NodeB output power of 20-40W, UE maximum transmit power of 21dBm, typical antenna gain of 17dBi, maximum path loss of 135-160dB, and TMA gain of 12dB from noise figure reduction.
3. Calcul
Turbo codes are a type of error correcting code that can achieve performance close to the theoretical maximum allowed by Shannon's limit. Turbo codes use an iterative decoding process between two recursive systematic convolutional encoders separated by an interleaver. This iterative decoding allows turbo codes to correct errors very efficiently. Turbo codes are used in applications like deep space communications and mobile phone networks due to their ability to operate reliably at low signal-to-noise ratios.
This document presents information on BCH codes and their decoding. It discusses how BCH codes were invented in 1959-1960 and provides an abstract stating that BCH codes form a class of cyclic error-correcting codes constructed using finite fields. Various decoding methods for BCH codes are then described, including Chien search, the Euclidean algorithm, and the Berlekamp-Massey algorithm. The document goes on to explain the general decoding process for BCH codes and provides an example. It also covers correcting errors and erasures for nonbinary BCH codes using the Euclidean algorithm, demonstrating with an example.
This document discusses digital signal processing (DSP). It begins by explaining that DSP involves converting an analog waveform into a series of discrete digital levels by measuring the amplitude of the waveform at regular intervals. It then provides examples of common DSP operations like convolution, correlation, filtering and modulation. The document notes key advantages of DSP like accuracy and reproducibility but also mentions disadvantages like cost and finite word length problems. It concludes by listing some common application areas for DSP like image processing, instrumentation/control, speech/audio processing, and telecommunications.
This document describes a Matlab Simulink simulation of frequency-shift keying (FSK) modulation and demodulation. The simulation implements binary FSK (BFSK) using blocks like a Bernoulli binary generator, switch, charge pump PLL, and scope. It aims to prove and easily implement BFSK modulation and demodulation on hardware. The simulation adds noise to make it more realistic. The conclusion verifies that the simulation demonstrates the phenomenon of BFSK.
The document discusses modulation and demodulation techniques used in RFIC design. It covers analog and digital modulation methods including AM, FM, ASK, FSK and PSK. It provides details on the implementation of various modulation schemes, their spectra, and detection methods. Key topics include amplitude modulation, frequency modulation, digital modulations, optimal detection using matched filters, ASK modulation characteristics and non-coherent/coherent detection.
This document discusses turbo and turbo-like codes. It begins with an introduction to turbo codes, describing them as a class of high-performance error correction codes that were the first practical codes to closely approach channel capacity. It then covers channel coding, Shannon's theory, existing coding schemes like block codes and convolutional codes, and the need for better codes. The document spends significant time explaining turbo codes in detail, including their structure using parallel concatenated convolutional codes, interleaving, and iterative decoding. It also discusses related coding schemes like turbo product codes and low-density parity check codes. Finally, it reviews the performance, practical issues, applications in standards, and future trends of turbo and turbo-like codes.
The document discusses key technologies in LTE including access techniques, MIMO, scheduling, link adaptation, and HARQ. It covers OFDM and SC-FDMA used for downlink and uplink access, benefits of MIMO including improved SINR and shared SINR through modes like transmit diversity, receive diversity, and spatial multiplexing. Scheduling considers factors like CQI and aims for fairness and throughput. Link adaptation uses CQI and MCS to optimize air interface efficiency. HARQ enables recovery of errors at the MAC layer through retransmissions.
The document discusses turbo codes, which are a type of error correction code that can achieve low bit error rates close to the Shannon limit. Turbo codes work by encoding the data using two or more simple component codes on interleaved versions of the input and then iteratively decoding the outputs of the component decoders. This iterative decoding allows turbo codes to outperform conventional codes with lower complexity. The document provides background on channel coding, forward error correction, and convolutional codes before explaining how turbo codes are constructed and decoded.
This document provides information on Allgon's 2100 MHz dual polarized antennas, including specifications for singleband and dualband antenna models. Key details include antenna gains ranging from 15.5 to 18 dBi, beamwidths of 65 degrees, VSWR and isolation values, mechanical specifications, typical radiation patterns, and filters for 1800/2100 MHz dualband operation.
CDMA is a digital cellular standard that allows multiple users to access the same radio frequency channel simultaneously through the use of unique code sequences. Users are separated by spreading their transmitted signals across the frequency band using pseudo-random codes. CDMA provides advantages over other multiple access techniques like FDMA and TDMA such as increased capacity, soft handoffs between cells, and covert operation due to its noise-like signals. The IS-95 standard introduced CDMA to cellular networks and specified the use of orthogonal codes to separate signals and a 1.25 MHz channel bandwidth to support multiple simultaneous voice calls.
This document discusses different techniques for achieving diversity in wireless communications and combining received signals:
1. Selection diversity techniques select the strongest signal from multiple antennas, either based on received signal strength (RSSI) or bit error rate (BER). Combining diversity techniques combine all received signals.
2. Combining diversity techniques include maximal ratio combining (MRC), which weights signals by amplitude, and equal gain combining (EGC), which weights all signals equally after phase correction. MRC achieves better performance than EGC when signals are highly faded.
3. The document compares the advantages and disadvantages of different selection criteria and combining techniques. It also describes switched and feedback selection diversity approaches.
1) The document discusses various digital modulation techniques including ASK, PSK, and FSK.
2) It provides details on the basic principles, modulation/demodulation methods, and spectra of these techniques.
3) Key aspects covered include the use of amplitude, phase, and frequency to encode digital signals for transmission, as well as synchronous and asynchronous detection methods.
Abhinav End Sem Presentation Software Defined Radioguestad4734
The document discusses the development of a wideband RF front end for software defined radios covering 400MHz to 3.4GHz. It describes the ideal SDR architecture, existing SDR implementations, and the objectives of developing a single wideband RF front end. The work done so far includes studying receiver architectures, designing a frequency synthesizer board, modeling amplifiers and mixers, and outlining future work on partitioning the frequency band and implementing filters and switches.
This document provides an overview of pulse amplitude modulation (PAM). It defines PAM as a modulation technique where the message information is encoded in the amplitude of a series of signal pulses. There are two types: single polarity PAM which adds a DC bias to ensure all pulses are positive, and double polarity PAM where pulses can be both positive and negative. PAM is used to modulate digital data transmission and involves sampling the message signal to vary the amplitude of a carrier pulse train. The modulated signal is then detected by measuring the amplitude level of each carrier pulse.
Fm transmitter and future radio technologyChima Chukwu
ABSTRACT
FM Transmitter is a device which generates frequency modulated signal. It is
one element of a radio system which, with the aid of an antenna, propagates
an electromagnetic signal. Standard FM broadcasts are based in the 88 - 108
MHz range. Advancements have been made in the way FM is broadcast. This
includes utilizing such technologies as Hybrid Digital (HD) Radio, Software
Defined Radio (SDR) and Cognitive Radio.
HD Radio uses IBOC (In-Band On-Channel) as a methodof broadcasting digital
radio signals on the same FM channel, and at the same time as the
conventional analog signal while Software defined radio (SDR) is the term used
to describe radio technology where some or the entire wireless physical layer
functions are software defined.
Cognitive radio networks on the other hand, are intelligent networks that can
automatically sense the environment and adapt the communication
parameters accordingly. These types of networks have applications in dynamic
spectrum access, co-existence of different wireless networks, interference
management, etc.
This document discusses green communication and summarizes several research papers on the topic. It outlines the objectives of green communication as protecting the environment from harmful EM radiation, reducing greenhouse gases, and reducing wireless network operational costs. It then summarizes several papers on topics like power control, resource allocation, power allocation, and massive MIMO. The document also discusses energy consumption in the ICT industry, wireless resource trading challenges, and open research areas in green communication like massive MIMO and cooperative communication. It presents two case studies analyzing the energy efficiency of massive MIMO systems with considerations for aspects like channel gain, number of antennas, and transceiver power consumption.
The global system for mobile communications (GSM) is a set of recommendations and specifications for a digital cellular telephone network (known as a Public Land Mobile Network, or PLMN). These recommendations ensure the compatibility of equipment from different GSM manufacturers, and interconnectivity between different administrations, including operations across international boundaries
The GSM network is comprised of the following components:
Network Elements
The GSM network incorporates a number of network elements to support mobile equipment. They are listed and described in the GSM network elements section of this chapter.
GSM subsystems
In addition, the network includes subsystems that are not formally recognized as network elements but are necessary for network operation. These are described in the GSM subsystems (non-network elements) section of this chapter.
Standardized Interfaces
GSM specifies standards for interfaces between network elements, which ensure the connectivity of GSM equipment from different manufacturers. These are listed in the Standardized interfaces section of this chapter.
Network Protocols
For most of the network communications on these interfaces, internationally recognized communications protocols have been used
These are identified in the Network protocols section of this chapter.
GSM Frequencies
The frequency allocations for GSM 900, Extended GSM and Digital Communications Systems are identified in the GSM frequencies section of this chapter.
BER performance simulation in a multi user MIMO PresentationVikas Pandey
This document summarizes a simulation of bit error rate (BER) performance for a multi-user MIMO system using transmit antenna selection/maximal ratio combining (TAS/MRC) over a Nakagami-m fading channel. Modulation schemes evaluated include BPSK, QPSK, and QAM. Simulations were conducted for systems with 200 and 500 users. Results show BER decreasing as the number of users increases or modulation order increases from BPSK to QAM. Findings can inform the design of future MIMO devices.
The document discusses different types of handovers in wireless networks. It defines handover as changing the point of connection between a mobile station and base stations. There are three types of handover decisions: network-controlled, mobile-assisted, and mobile-controlled. The document also describes hard handover, soft handover, horizontal handover, and vertical handover. It explains the mechanisms and characteristics of each type of handover.
The Presentation includes Basics of Non - Uniform Quantization, Companding and different Pulse Code Modulation Techniques. Comparison of Various PCM techniques is done considering various Parameters in Communication Systems.
This document provides an overview of Reed-Solomon codes and convolutional codes. It describes the key properties and components of Reed-Solomon codes, including how they encode messages by dividing them into blocks and adding redundancy. It also explains convolutional codes use shift registers and linear algebraic functions to encode redundant information. The document compares block and convolutional codes and discusses factors like coding rate and constraint length that impact their performance.
This document discusses the effect of feedback on distortion in electronic circuits. It shows that negative feedback reduces harmonic distortion by making the circuit appear more linear. Specifically:
- Feedback can null out third-order distortion by adjusting the feedback level to satisfy an equation.
- For a given output signal level, feedback reduces second-order distortion by a factor of 1/(1+T) where T is the loop gain.
- Emitter degeneration in a BJT amplifier has the same effect as negative feedback, where the degeneration resistance RE acts as the feedback factor.
This document summarizes key concepts about distortion metrics from a lecture on distortion in electronics circuits and systems. It discusses different types of distortion such as harmonic distortion, intermodulation distortion, and cross modulation. It provides mathematical definitions for metrics like total harmonic distortion, second order intermodulation distortion, and third order intermodulation distortion. Examples of distortion in common systems like low-IF receivers, AM signals, and BJT amplifiers are also summarized.
This document presents information on BCH codes and their decoding. It discusses how BCH codes were invented in 1959-1960 and provides an abstract stating that BCH codes form a class of cyclic error-correcting codes constructed using finite fields. Various decoding methods for BCH codes are then described, including Chien search, the Euclidean algorithm, and the Berlekamp-Massey algorithm. The document goes on to explain the general decoding process for BCH codes and provides an example. It also covers correcting errors and erasures for nonbinary BCH codes using the Euclidean algorithm, demonstrating with an example.
This document discusses digital signal processing (DSP). It begins by explaining that DSP involves converting an analog waveform into a series of discrete digital levels by measuring the amplitude of the waveform at regular intervals. It then provides examples of common DSP operations like convolution, correlation, filtering and modulation. The document notes key advantages of DSP like accuracy and reproducibility but also mentions disadvantages like cost and finite word length problems. It concludes by listing some common application areas for DSP like image processing, instrumentation/control, speech/audio processing, and telecommunications.
This document describes a Matlab Simulink simulation of frequency-shift keying (FSK) modulation and demodulation. The simulation implements binary FSK (BFSK) using blocks like a Bernoulli binary generator, switch, charge pump PLL, and scope. It aims to prove and easily implement BFSK modulation and demodulation on hardware. The simulation adds noise to make it more realistic. The conclusion verifies that the simulation demonstrates the phenomenon of BFSK.
The document discusses modulation and demodulation techniques used in RFIC design. It covers analog and digital modulation methods including AM, FM, ASK, FSK and PSK. It provides details on the implementation of various modulation schemes, their spectra, and detection methods. Key topics include amplitude modulation, frequency modulation, digital modulations, optimal detection using matched filters, ASK modulation characteristics and non-coherent/coherent detection.
This document discusses turbo and turbo-like codes. It begins with an introduction to turbo codes, describing them as a class of high-performance error correction codes that were the first practical codes to closely approach channel capacity. It then covers channel coding, Shannon's theory, existing coding schemes like block codes and convolutional codes, and the need for better codes. The document spends significant time explaining turbo codes in detail, including their structure using parallel concatenated convolutional codes, interleaving, and iterative decoding. It also discusses related coding schemes like turbo product codes and low-density parity check codes. Finally, it reviews the performance, practical issues, applications in standards, and future trends of turbo and turbo-like codes.
The document discusses key technologies in LTE including access techniques, MIMO, scheduling, link adaptation, and HARQ. It covers OFDM and SC-FDMA used for downlink and uplink access, benefits of MIMO including improved SINR and shared SINR through modes like transmit diversity, receive diversity, and spatial multiplexing. Scheduling considers factors like CQI and aims for fairness and throughput. Link adaptation uses CQI and MCS to optimize air interface efficiency. HARQ enables recovery of errors at the MAC layer through retransmissions.
The document discusses turbo codes, which are a type of error correction code that can achieve low bit error rates close to the Shannon limit. Turbo codes work by encoding the data using two or more simple component codes on interleaved versions of the input and then iteratively decoding the outputs of the component decoders. This iterative decoding allows turbo codes to outperform conventional codes with lower complexity. The document provides background on channel coding, forward error correction, and convolutional codes before explaining how turbo codes are constructed and decoded.
This document provides information on Allgon's 2100 MHz dual polarized antennas, including specifications for singleband and dualband antenna models. Key details include antenna gains ranging from 15.5 to 18 dBi, beamwidths of 65 degrees, VSWR and isolation values, mechanical specifications, typical radiation patterns, and filters for 1800/2100 MHz dualband operation.
CDMA is a digital cellular standard that allows multiple users to access the same radio frequency channel simultaneously through the use of unique code sequences. Users are separated by spreading their transmitted signals across the frequency band using pseudo-random codes. CDMA provides advantages over other multiple access techniques like FDMA and TDMA such as increased capacity, soft handoffs between cells, and covert operation due to its noise-like signals. The IS-95 standard introduced CDMA to cellular networks and specified the use of orthogonal codes to separate signals and a 1.25 MHz channel bandwidth to support multiple simultaneous voice calls.
This document discusses different techniques for achieving diversity in wireless communications and combining received signals:
1. Selection diversity techniques select the strongest signal from multiple antennas, either based on received signal strength (RSSI) or bit error rate (BER). Combining diversity techniques combine all received signals.
2. Combining diversity techniques include maximal ratio combining (MRC), which weights signals by amplitude, and equal gain combining (EGC), which weights all signals equally after phase correction. MRC achieves better performance than EGC when signals are highly faded.
3. The document compares the advantages and disadvantages of different selection criteria and combining techniques. It also describes switched and feedback selection diversity approaches.
1) The document discusses various digital modulation techniques including ASK, PSK, and FSK.
2) It provides details on the basic principles, modulation/demodulation methods, and spectra of these techniques.
3) Key aspects covered include the use of amplitude, phase, and frequency to encode digital signals for transmission, as well as synchronous and asynchronous detection methods.
Abhinav End Sem Presentation Software Defined Radioguestad4734
The document discusses the development of a wideband RF front end for software defined radios covering 400MHz to 3.4GHz. It describes the ideal SDR architecture, existing SDR implementations, and the objectives of developing a single wideband RF front end. The work done so far includes studying receiver architectures, designing a frequency synthesizer board, modeling amplifiers and mixers, and outlining future work on partitioning the frequency band and implementing filters and switches.
This document provides an overview of pulse amplitude modulation (PAM). It defines PAM as a modulation technique where the message information is encoded in the amplitude of a series of signal pulses. There are two types: single polarity PAM which adds a DC bias to ensure all pulses are positive, and double polarity PAM where pulses can be both positive and negative. PAM is used to modulate digital data transmission and involves sampling the message signal to vary the amplitude of a carrier pulse train. The modulated signal is then detected by measuring the amplitude level of each carrier pulse.
Fm transmitter and future radio technologyChima Chukwu
ABSTRACT
FM Transmitter is a device which generates frequency modulated signal. It is
one element of a radio system which, with the aid of an antenna, propagates
an electromagnetic signal. Standard FM broadcasts are based in the 88 - 108
MHz range. Advancements have been made in the way FM is broadcast. This
includes utilizing such technologies as Hybrid Digital (HD) Radio, Software
Defined Radio (SDR) and Cognitive Radio.
HD Radio uses IBOC (In-Band On-Channel) as a methodof broadcasting digital
radio signals on the same FM channel, and at the same time as the
conventional analog signal while Software defined radio (SDR) is the term used
to describe radio technology where some or the entire wireless physical layer
functions are software defined.
Cognitive radio networks on the other hand, are intelligent networks that can
automatically sense the environment and adapt the communication
parameters accordingly. These types of networks have applications in dynamic
spectrum access, co-existence of different wireless networks, interference
management, etc.
This document discusses green communication and summarizes several research papers on the topic. It outlines the objectives of green communication as protecting the environment from harmful EM radiation, reducing greenhouse gases, and reducing wireless network operational costs. It then summarizes several papers on topics like power control, resource allocation, power allocation, and massive MIMO. The document also discusses energy consumption in the ICT industry, wireless resource trading challenges, and open research areas in green communication like massive MIMO and cooperative communication. It presents two case studies analyzing the energy efficiency of massive MIMO systems with considerations for aspects like channel gain, number of antennas, and transceiver power consumption.
The global system for mobile communications (GSM) is a set of recommendations and specifications for a digital cellular telephone network (known as a Public Land Mobile Network, or PLMN). These recommendations ensure the compatibility of equipment from different GSM manufacturers, and interconnectivity between different administrations, including operations across international boundaries
The GSM network is comprised of the following components:
Network Elements
The GSM network incorporates a number of network elements to support mobile equipment. They are listed and described in the GSM network elements section of this chapter.
GSM subsystems
In addition, the network includes subsystems that are not formally recognized as network elements but are necessary for network operation. These are described in the GSM subsystems (non-network elements) section of this chapter.
Standardized Interfaces
GSM specifies standards for interfaces between network elements, which ensure the connectivity of GSM equipment from different manufacturers. These are listed in the Standardized interfaces section of this chapter.
Network Protocols
For most of the network communications on these interfaces, internationally recognized communications protocols have been used
These are identified in the Network protocols section of this chapter.
GSM Frequencies
The frequency allocations for GSM 900, Extended GSM and Digital Communications Systems are identified in the GSM frequencies section of this chapter.
BER performance simulation in a multi user MIMO PresentationVikas Pandey
This document summarizes a simulation of bit error rate (BER) performance for a multi-user MIMO system using transmit antenna selection/maximal ratio combining (TAS/MRC) over a Nakagami-m fading channel. Modulation schemes evaluated include BPSK, QPSK, and QAM. Simulations were conducted for systems with 200 and 500 users. Results show BER decreasing as the number of users increases or modulation order increases from BPSK to QAM. Findings can inform the design of future MIMO devices.
The document discusses different types of handovers in wireless networks. It defines handover as changing the point of connection between a mobile station and base stations. There are three types of handover decisions: network-controlled, mobile-assisted, and mobile-controlled. The document also describes hard handover, soft handover, horizontal handover, and vertical handover. It explains the mechanisms and characteristics of each type of handover.
The Presentation includes Basics of Non - Uniform Quantization, Companding and different Pulse Code Modulation Techniques. Comparison of Various PCM techniques is done considering various Parameters in Communication Systems.
This document provides an overview of Reed-Solomon codes and convolutional codes. It describes the key properties and components of Reed-Solomon codes, including how they encode messages by dividing them into blocks and adding redundancy. It also explains convolutional codes use shift registers and linear algebraic functions to encode redundant information. The document compares block and convolutional codes and discusses factors like coding rate and constraint length that impact their performance.
This document discusses the effect of feedback on distortion in electronic circuits. It shows that negative feedback reduces harmonic distortion by making the circuit appear more linear. Specifically:
- Feedback can null out third-order distortion by adjusting the feedback level to satisfy an equation.
- For a given output signal level, feedback reduces second-order distortion by a factor of 1/(1+T) where T is the loop gain.
- Emitter degeneration in a BJT amplifier has the same effect as negative feedback, where the degeneration resistance RE acts as the feedback factor.
This document summarizes key concepts about distortion metrics from a lecture on distortion in electronics circuits and systems. It discusses different types of distortion such as harmonic distortion, intermodulation distortion, and cross modulation. It provides mathematical definitions for metrics like total harmonic distortion, second order intermodulation distortion, and third order intermodulation distortion. Examples of distortion in common systems like low-IF receivers, AM signals, and BJT amplifiers are also summarized.
Lecture Notes: EEEE6490345 RF and Microwave Electronics - Noise In Two-Port ...AIMST University
The document discusses noise in two-port networks. It defines noise figure as the ratio of signal-to-noise ratio at the input to the output. Noise figure depends on the noise added by the two-port network and any internal noise. The noise figure of multiple cascaded stages is calculated by adding the noise figure of each stage while accounting for the gain of previous stages. Noise circles are plotted on the Smith chart to visualize the noise figure as a function of source impedance matching. Examples calculate the noise figure of amplifier cascades and radio frequency receivers.
This document contains notes on probability theory from a course. It begins with definitions of measures, σ-algebras, Borel σ-algebras, and related concepts. It then proves some key properties, including that the Borel σ-algebra on the real line can be generated by open intervals with rational endpoints. The document also contains proofs showing when two measures are equal and the Monotone Class Theorem for sets.
This document contains solutions to multiple problems involving slip-line field analysis. Problem 9-14 asks about a slip-line field for extrusion or drawing where r=0.0760 and α=15°. For extrusion, the stress σ2 at point 4,5 is found to be 1.842(2k). For drawing, σ2 would have the same magnitude but opposite sign. The product may depend on whether it is an extrusion or drawing, as extrusion would result in a thicker product while drawing a thinner product.
This document discusses digital modulation techniques. It begins by explaining why digital modulation is needed to transmit digital signals over long distances. It then provides a block diagram of a digital communication system and discusses geometric representation of signals using multidimensional vectors. The document explains concepts like signal constellations, decision regions, error probability, and provides examples of modulation techniques including BPSK, BFSK, and differential PSK. It compares the energy efficiency of BPSK and BFSK.
This document provides an overview of frequency response and analysis for amplifiers. It discusses:
- How the voltage gain of an amplifier decreases at low and high frequencies due to external and internal capacitances.
- Key terms like cutoff frequencies (f1 and f2), midband, and roll-off factor.
- Methods for analyzing the frequency response of BJT and JFET amplifier stages to determine dominant capacitances and calculate cutoff frequencies.
- Examples are provided to demonstrate the analysis process.
The document covers frequency response fundamentals and analysis techniques for characterizing amplifier performance over a range of frequencies.
Types of Multistage Transistor Amplifierssherifhanafy4
A multistage transistor amplifier uses multiple single amplifier stages connected in cascade through a coupling device. The coupling device transfers the AC output of one stage to the input of the next while isolating the DC. Common coupling methods include RC coupling using a capacitor, transformer coupling, and direct coupling without isolation. Transformer coupling provides impedance matching between stages for increased voltage and power gain compared to RC coupling, making it suitable for power amplification applications.
This document presents two methods for calculating voltage drop in road lighting systems: an approximate method and a precise method. The precise method divides the calculation into voltage drop in the phase conductor and in the neutral conductor. It then derives a generalized formula to calculate the voltage drop for any number of light poles. Two examples applying both methods are worked out, showing the precise method provides a less conservative result than the approximate method. The conclusion recommends using the precise method for more accuracy when voltage drop is critical.
1. The document provides solutions to multiple choice questions from an AP Physics B exam in 1998. It explains the basic ideas and solutions for 27 multiple choice questions covering topics like kinematics, forces, energy, momentum, circuits, fields, and more. The solutions are concise and directly address the key principles or calculations required to solve each problem.
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Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
1. EECS 142
Lecture 9: Intercept Point, Gain Compression and
Blocking
Prof. Ali M. Niknejad
University of California, Berkeley
Copyright c 2005 by Ali M. Niknejad
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 1/29 – p. 1
2. Gain Compression
Vi
Vo
dVo
dVi
Vi
Vo
dVo
dVi
The large signal input/output relation can display gain
compression or expansion. Physically, most amplifier
experience gain compression for large signals.
The small-signal gain is related to the slope at a given
point. For the graph on the left, the gain decreases for
increasing amplitude.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 2/29 – p. 2
3. 1 dB Compression Point
¯
¯
¯
¯
Vo
Vi
¯
¯
¯
¯
Vi
Po,−1 dB
Pi,−1 dB
Gain compression occurs because eventually the
output signal (voltage, current, power) limits, due to the
supply voltage or bias current.
If we plot the gain (log scale) as a function of the input
power, we identify the point where the gain has dropped
by 1 dB. This is the 1 dB compression point. It’s a very
important number to keep in mind.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 3/29 – p. 3
4. Apparent Gain
Recall that around a small deviation, the large signal
curve is described by a polynomial
so = a1si + a2s2
i + a3s3
i + · · ·
For an input si = S1 cos(ω1t), the cubic term generates
S3
1 cos3
(ω1t) = S3
1 cos(ω1t)
1
2
(1 + cos(2ω1t))
= S3
1
1
2
cos(ω1t) +
2
4
cos(ω1t) cos(2ω1t)
Recall that 2 cos a cos b = cos(a + b) + cos(a − b)
= S3
1
1
2
cos(ω1t) +
1
4
(cos(ω1t) + cos(3ω1t))
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 4/29 – p. 4
5. Apparent Gain (cont)
Collecting terms
= S3
1
3
4
cos(ω1t) +
1
4
cos(3ω1t)
The apparent gain of the system is therefor
G =
So,ω1
Si,ω1
=
a1S1 + 3
4a3S3
1
S1
= a1 +
3
4
a3S2
1 = a1
1 +
3
4
a3
a1
S2
1
= G(S1)
If a3/a1 0, the gain compresses with increasing
amplitude.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 5/29 – p. 5
6. 1-dB Compression Point
Let’s find the input level where the gain has dropped by
1 dB
20 log
1 +
3
4
a3
a1
S2
1
= −1 dB
3
4
a3
a1
S2
1 = −0.11
S1 =
s
4
3
a1
a3
×
√
0.11 = IIP3 − 9.6 dB
The term in the square root is called the third-order
intercept point (see next few slides).
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 6/29 – p. 6
7. Intercept Point IP2
-50 -40 -30 -20 -10
-40
-30
-20
-10
0
dBc
IP2
Pin
(dBm)
Pout
(dBm)
IIP2
OIP2
dBc
10
20
10
Fund
2
n
d
The extrapolated point where IM2 = 0 dBc is known as
the second order intercept point IP2.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 7/29 – p. 7
8. Properties of Intercept Point IP2
Since the second order IM distortion products increase
like s2
i , we expect that at some power level the distortion
products will overtake the fundamental signal.
The extrapolated point where the curves of the
fundamental signal and second order distortion product
signal meet is the Intercept Point (IP2).
At this point, then, by definition IM2 = 0 dBc.
The input power level is known as IIP2, and the output
power when this occurs is the OIP2 point.
Once the IP2 point is known, the IM2 at any other
power level can be calculated. Note that for a dB
back-off from the IP2 point, the IM2 improves dB for dB
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 8/29 – p. 8
9. Intercept Point IP3
-50 -40 -30 -20 -10
-30
-20
-10
0
10
dBc
IP3
Pin
(dBm)
Pout
(dBm)
IIP3
OIP3
dBc
20
Fund
T
h
i
r
d
The extrapolated point where IM3 = 0 dBc is known as
the third-order intercept point IP3.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 9/29 – p. 9
10. Properties of Intercept Point IP3
Since the third order IM distortion products increase like
s3
i , we expect that at some power level the distortion
products will overtake the fundamental signal.
The extrapolated point where the curves of the
fundamental signal and third order distortion product
signal meet is the Intercept Point (IP3).
At this point, then, by definition IM3 = 0 dBc.
The input power level is known as IIP3, and the output
power when this occurs is the OIP3 point.
Once the IP3 point is known, the IM3 at any other
power level can be calculated. Note that for a 10 dB
back-off from the IP3 point, the IM3 improves 20 dB.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 10/29 – p.
11. Intercept Point Example
From the previous graph we see that our amplifier has
an IIP3 = −10 dBm.
What’s the IM3 for an input power of Pin = −20 dBm?
Since the IM3 improves by 20 dB for every 10 dB
back-off, it’s clear that IM3 = 20 dBc
What’s the IM3 for an input power of Pin = −110 dBm?
Since the IM3 improves by 20 dB for every 10 dB
back-off, it’s clear that IM3 = 200 dBc
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 11/29 – p.
12. Calculated IIP2/IIP3
We can also calculate the IIP points directly from our
power series expansion. By definition, the IIP2 point
occurs when
IM2 = 1 =
a2
a1
Si
Solving for the input signal level
IIP2 = Si =
a1
a2
In a like manner, we can calculate IIP3
IM3 = 1 =
3
4
a3
a1
S2
i IIP3 = Si =
s
4
3
a1
a3
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 12/29 – p.
13. Blocker or Jammer
Signal
Interference
channel
LNA
Consider the input spectrum of a weak desired signal
and a “blocker”
Si = S1 cos ω1t
| {z }
Blocker
+ s2 cos ω2t
| {z }
Desired
We shall show that in the presence of a strong
interferer, the gain of the system for the desired signal
is reduced. This is true even if the interference signal is
at a substantially difference frequency. We call this
interference signal a “jammer”.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 13/29 – p.
14. Blocker (II)
Obviously, the linear terms do not create any kind of
desensitization. The second order terms, likewise,
generate second harmonic and intermodulation, but not
any fundamental signals.
In particular, the cubic term a3S3
i generates the jammer
desensitization term
S3
i = S3
1 cos3
ω1t + s3
2 cos3
ω2t + 3S2
1s2 cos2
ω1t cos ω2t+
3s2
1S2 cos2
ω2t cos ω1t
The first two terms generate cubic and third harmonic.
The last two terms generate fundamental signals at ω1
and ω2. The last term is much smaller, though, since
s2 ≪ S1.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 14/29 – p.
15. Blocker (III)
The blocker term is therefore given by
a33S2
1s2
1
2
cos ω2t
This term adds or subtracts from the desired signal.
Since a3 0 for most systems (compressive
non-linearity), the effect of the blocker is to reduce the
gain
App Gain =
a1s2 + a3
3
2S2
1s2
s2
= a1 + a3
3
2
S2
1 = a1
1 +
3
2
a3
a1
S2
1
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 15/29 – p.
16. Out of Band 3 dB Desensitization
Let’s find the blocker power necessary to desensitize
the amplifier by 3 dB. Solving the above equation
20 log
1 +
3
2
a3
a1
S2
1
= −3 dB
We find that the blocker power is given by
POB = P−1 dB + 1.2 dB
It’s now clear that we should avoid operating our
amplifier with any signals in the vicinity of P−1 dB, since
gain reduction occurs if the signals are larger. At this
signal level there is also considerable intermodulation
distortion.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 16/29 – p.
17. Series Inversion
Often it’s easier to find a power series relation for the
input in terms of the output. In other words
Si = a1So + a2S2
o + a3S3
o + · · ·
But we desire the inverse relation
So = b1Si + b2S2
i + b3S3
i + · · ·
To find the inverse relation, we can substitute the above
equation into the original equation and equate
coefficient of like powers.
Si = a1(b1Si + b2S2
i + b3S3
i + · · · ) + a2( )2
+ a3( )3
+ · · ·
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 17/29 – p.
18. Inversion (cont)
Equating linear terms, we find, as expected, that
a1b1 = 1, or b1 = 1/a1.
Equating the square terms, we have
0 = a1b2 + a2b2
1
b2 = −
a2b2
1
a1
= −
a2
a3
1
Finally, equating the cubic terms we have
0 = a1b3 + a22b1b2 + a3b3
1
b3 =
2a2
2
a5
1
−
a3
a4
1
It’s interesting to note that if one power series does not
have cubic, a3 ≡ 0, the inverse series has cubic due to
the first term above.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 18/29 – p.
19. Cascade
IIP2A
IIP3A
IIP2B
IIP3B
IIP2
IIP3
GA
V
GA
P
Another common situation is that we cascade two
non-linear systems, as shown above. we have
y = f(x) = a1x + a2x2
+ a3x3
+ · · ·
z = g(y) = b1y + b2y2
+ b3y3
+ · · ·
We’d like to find the overall relation
z = c1x + c2x2
+ c3x3
+ · · ·
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 19/29 – p.
20. Cascade Power Series
To find c1, c2, · · · , we simply substitute one power series
into the other and collect like powers.
The linear terms, as expected, are given by
c1 = b1a1 = a1b1
The square terms are given by
c2 = b1a2 + b2a2
1
The first term is simply the second order distortion
produced by the first amplifier and amplified by the
second amplifier linear term. The second term is the
generation of second order by the second amplifier.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 20/29 – p.
21. Cascade Cubic
Finally, the cubic terms are given by
c3 = b1a3 + b22a1a2 + b3a3
1
The first and last term have a very clear origin. The
middle terms, though, are more interesting. They arise
due to second harmonic interaction. The second order
distortion of the first amplifier can interact with the linear
term through the second order non-linearity to produce
cubic distortion.
Even if both amplifiers have negligible cubic,
a3 = b3 ≡ 0, we see the overall amplifier can generate
cubic through this mechanism.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 21/29 – p.
22. Cascade Example
In the above amplifier, we can decompose the
non-linearity as a cascade of two non-linearities, the Gm
non-linearity
id = Gm1vin + Gm2v2
in + Gm3v3
in + · · ·
And the output impedance non-linearity
vo = R1id + R2i2
d + R3i3
d + · · ·
The output impedance can be a non-linear resistor load
(such as a current mirror) or simply the load of the
device itself, which has a non-linear component.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 22/29 – p.
23. IIP2 Cascade
Commonly we’d like to know the performance of a
cascade in terms of the overall IIP2. To do this, note
that IIP2 = c1/c2
c2
c1
=
b1a2 + b2a2
1
b1a1
=
a2
a1
+
b2
b1
a1
This leads to
1
IIP2
=
1
IIP2A
+
a1
IIP2B
This is a very intuitive result, since it simply says that
we can input refer the IIP2 of the second amplifier to
the input by the voltage gain of the first amplifier.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 23/29 – p.
24. IIP2 Cascade Example
Example 1: Suppose the input amplifiers of a cascade
has IIP2A = +0 dBm and a voltage gain of 20 dB. The
second amplifier has IIP2B = +10 dBm.
The input referred IIP2B
i = 10 dBm − 20 dB = −10 dBm
This is a much smaller signal than the IIP2A, so clearly
the second amplifier dominates the distortion. The
overall distortion is given by IIP2 ≈ −12 dB.
Example 2: Now suppose IIP2B = +20 dBm. Since
IIP2B
i = 20 dBm − 20 dB = 0 dBm, we cannot assume
that either amplifier dominates.
Using the formula, we see the actual IIP2 of the
cascade is a factor of 2 down, IIP2 = −3 dBm.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 24/29 – p.
25. IIP3 Cascade
Using the same approach, let’s start with
c3
c1
=
b1a3 + b2a1a22 + b3a3
1
baa1
=
a3
a1
+
b3
b1
a2
1 +
b2
b1
2a2
The last term, the second harmonic interaction term,
will be neglected for simplicity. Then we have
1
IIP32
=
1
IIP32
A
+
a2
1
IIP32
B
Which shows that the IIP3 of the second amplifier is
input referred by the voltage gain squared, or the power
gain.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 25/29 – p.
26. LNA/Mixer Example
A common situation is an LNA and mixer cascade. The
mixer can be characterized as a non-linear block with a
given IIP2 and IIP3.
In the above example, the LNA has an
IIP3A = −10 dBm and a power gain of 20 dB. The mixer
has an IIP3B = −20 dBm.
If we input refer the mixer, we have
IIP3B
i = −20 dBm − 20 dB = −40 dBm.
The mixer will dominate the overall IIP3 of the system.
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 26/29 – p.
27. Example: Disto in Long-Ch. MOS Amp
vi
VQ
ID = IQ + io
ID = 1
2µCox
W
L
(VGS − VT )2
io +IQ = 1
2µCox
W
L
(VQ +vi −VT )2
Ignoring the output impedance we have
= 1
2µCox
W
L
(VQ − VT )2
+ v2
i + 2vi(VQ − VT )
= IQ
|{z}
dc
+ µCox
W
L
vi(VQ − VT )
| {z }
linear
+ 1
2µCox
W
L
v2
i
| {z }
quadratic
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 27/29 – p.
28. Ideal Square Law Device
An ideal square law device only generates 2nd order
distortion
io = gmvi + 1
2µCox
W
L
v2
i
a1 = gm
a2 = 1
2µCox
W
L
= 1
2
gm
VQ − VT
a3 ≡ 0
The harmonic distortion is given by
HD2 =
1
2
a2
a1
vi =
1
4
gm
VQ − VT
1
gm
vi =
1
4
vi
VQ − VT
HD3 = 0
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 28/29 – p.
29. Real MOSFET Device
0
200
400
600
Effective Field
Mobility
Triode CLM DIBL SCBE
R
out
kΩ
Vds (V)
2
4
6
8
10
12
14
0 1 2 3 4
The real MOSFET device generates higher order
distortion
The output impedance is non-linear. The mobility µ is
not a constant but a function of the vertical and
horizontal electric field
We may also bias the device at moderate or weak
inversion, where the device behavior is more
exponential
There is also internal feedback
A. M. Niknejad University of California, Berkeley EECS 142 Lecture 9 p. 29/29 – p.