The cellular concept was developed to solve the problem of spectral congestion. It uses multiple low-power transmitters to provide coverage over small areas rather than single high-power transmitters. Neighboring cells are assigned different channel groups to minimize interference, and the same channel sets are reused at greater distances. When designing cellular systems, factors like geographical separation, shadowing effects, and user density must be considered to allow efficient frequency reuse while controlling interference.
In this chapter we examine the capacity of a single-user wireless channel where transmitter and/or receiver have a single antenna. We will discuss capacity for channels that are both time invariant and time varying. We first look at the well-known formula for capacity of a time-invariant additive white Gaussian noise (AWGN) channel and then consider capacity of time-varying flat fading channels. We will first consider flat fading channel capacity where only the fading distribution is known at the transmitter and receiver. We will also treat capacity of frequency-selective fading channels. For time -invariant frequency-selective channels the capacity is known and is achieved with an optimal power allocation that water-fills over frequency instead of time. We will consider only discrete-time systems in this chapter.
Basic cellular system, cellular system, What is cellular system, Generations of cellular system, Features of cellular systems, Shape of cells, Types of Basic cellular systems, Types of cellular systems, Circuit-Switched Systems, Analog cellular system, Analog cellular system, Digital Systems , Packet-switched system, 1g, 2g, 3g, 4g, 5g, MGCGV, Shubham Mishra
In this chapter we examine the capacity of a single-user wireless channel where transmitter and/or receiver have a single antenna. We will discuss capacity for channels that are both time invariant and time varying. We first look at the well-known formula for capacity of a time-invariant additive white Gaussian noise (AWGN) channel and then consider capacity of time-varying flat fading channels. We will first consider flat fading channel capacity where only the fading distribution is known at the transmitter and receiver. We will also treat capacity of frequency-selective fading channels. For time -invariant frequency-selective channels the capacity is known and is achieved with an optimal power allocation that water-fills over frequency instead of time. We will consider only discrete-time systems in this chapter.
Basic cellular system, cellular system, What is cellular system, Generations of cellular system, Features of cellular systems, Shape of cells, Types of Basic cellular systems, Types of cellular systems, Circuit-Switched Systems, Analog cellular system, Analog cellular system, Digital Systems , Packet-switched system, 1g, 2g, 3g, 4g, 5g, MGCGV, Shubham Mishra
This PPT contais hard ware requirement of GPS system, calculatin user position, pseudo range measurement, and calculation in spherical co-ordinate systems. rest is in basics of GPS -2.
INTRODUCTION
A chopper is a static device which is used to obtain a variable dc voltage from a
constant dc voltage source. A chopper is also known as dc-to-dc converter. The thyristor converter offers greater efficiency, faster response, lower maintenance, smaller size and smooth control. Choppers are widely used in trolley cars, battery operated vehicles, traction motor control, control of large number of dc motors, etc….. They are also used in regenerative braking of dc motors to return energy back to supply and also as dc voltage regulators.
Choppers are of two types
• Step-down choppers
• Step-up choppers.
In step-down choppers, the output voltage will be less than the input voltage
whereas in step-up choppers output voltage will be more than the input voltage.
Classification of Choppers:
(a) Depending upon the direction of the output current and voltage, the converters can be classified into five classes namely Class A [One-quadrant Operation] Class B [One-quadrant Operation] Class C [Two-quadrant Operation] Class D [Two-quadrant Operation] Class E [Four-quadrant Operation]
(b) Based on the output voltage of the output, the choppers are classified as
(i) Step-Down Chopper In this case the average output voltage is less than the input voltage. It is also known as step down converter
(ii) Step-Up Chopper Here the average output voltage is more than the input voltage. It is also known as step up converter
(iii) Step-Up/Down Chopper This type of converter produces an output voltage that is either lower or higher than the input voltage
(c) Depending upon the power loss occurred during turn ON/OFF of the switching device, the choppers are classified into two categories namely
(i) Hard switched Converter Here the power loss is high during the switching (ON to OFF and OFF to ON) as a result of the non zero voltage and current on the power switches.
(ii) Soft switched or resonant converters In this type of choppers, the power loss is low at the time of switching as a result of zero voltage and/or zero current on the switches.
2
PRINCIPLE OF STEP-DOWN CHOPPER
Figure 2.1 shows a step-down chopper with resistive load. The thyristor in the
circuit acts as a switch. When thyristor is ON, supply voltage appears across the load and
when thyristor is OFF, the voltage across the load will be zero. The output voltage and
current waveforms are as shown in figure 2.2.
-introduction:
Many of the people have a phobia of darkness, so to assist them in such situation, we have explained a simple circuit. It will automatically turn on street light in the way of LEDs or bulb coupled with relay.
Automatic street light system is very common nowadays as it provides intelligent street lighting mechanism. It provides light automatically during night without any human interference. These energy saving street lights make use of incandescent lamps instead of LEDs .So here I will study with you how to make an electronic circuit for street light automation using simple electronics component .
- Objectives of the Project
Reducing the wastage of power
Reducing physical efforts
Improve the system in our daily life
-CIRCUIT WORK PRINCIPLE:
The lamp(street bulb) should remain OFF during daytime and turn ON automatically during night. The unique property of light depended resistor is utilized here. LDR is a variable resistor which has very low resistance in the presence of light and very high resistance in the absence of light.In this circuit, we create a potential divider network with an ordinary resistor in one arm and a LDR on the other arm. According to Ohm’s law (V=IR), voltage drop across the resistor increases when its resistance increases. Here the drop across LDR varies with changes in light intensity. That is voltage drop across the LDR is minimum in the presence of light and maximum in the absence of light
A DISTRIBUTED DYNAMIC CHANNEL ALLOCATION IN CELLULAR COMMUNICATIONcscpconf
Now a days, mobile users are growing rapidly and the available frequency spectrum is limited.
Therefore the available spectrum must be efficiently utilized. In response a large number of
channel assignment and allocation policies have been proposed. Mostly Dynamic Channel
Allocation (DCA) has become an important subject of research and development for cellular
networks. In this paper, we propose a distributed dynamic channel allocation (DDCA)
algorithm for originating calls. This algorithm is executed at each base station and to allocate
the channel to mobile station, base station communicates with each other. In DDCA, the total
number of channels is divided into three groups. Any cell in the cluster can acquire the channel
group as long as no one of its adjacent cells is holding the same group. Due to this the cochannel
interference is avoided. The result show blocking rate of distributed dynamic channel allocation is reduced as compared to dynamic channel allocation algorithm with non-uniform traffic distribution
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
SAP Sapphire 2024 - ASUG301 building better apps with SAP Fiori.pdfPeter Spielvogel
Building better applications for business users with SAP Fiori.
• What is SAP Fiori and why it matters to you
• How a better user experience drives measurable business benefits
• How to get started with SAP Fiori today
• How SAP Fiori elements accelerates application development
• How SAP Build Code includes SAP Fiori tools and other generative artificial intelligence capabilities
• How SAP Fiori paves the way for using AI in SAP apps
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GraphSummit Singapore | The Future of Agility: Supercharging Digital Transfor...Neo4j
Leonard Jayamohan, Partner & Generative AI Lead, Deloitte
This keynote will reveal how Deloitte leverages Neo4j’s graph power for groundbreaking digital twin solutions, achieving a staggering 100x performance boost. Discover the essential role knowledge graphs play in successful generative AI implementations. Plus, get an exclusive look at an innovative Neo4j + Generative AI solution Deloitte is developing in-house.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
2. Cellular Systems--Cellular Concepts
The cellular concept was a major breakthrough in solving the
problem of spectral congestion and user capacity. It offered very
high capacity in a limited spectrum allocation without any major
technological changes.
The cellular concept has the following system level ideas
Replacing a single, high power transmitter with many low power
transmitters, each providing coverage to only a small area.
Neighboring cells are assigned different groups of channels in order to
minimize interference.
The same set of channels is then reused at different geographical
locations.
12/24/2013
Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
2
3. When designing a cellular mobile communication system, it is
important to provide good coverage and services in a high
user-density area.
Reuse can be done once the total interference from all users in
the cells using the same frequency (co-channel cell) for
transmission suffers from sufficient attenuation. Factors need
to be considered include:
Geographical separation (path loss)
Shadowing effect
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Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
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4. Cell Footprint
The actual radio coverage of a cell is known as the
cell footprint.
Irregular cell structure and irregular placing of the
transmitter may be acceptable in the initial system
design. However as traffic grows, where new cells
and channels need to be added, it may lead to
inability to reuse frequencies because of cochannel interference.
For systematic cell planning, a regular shape is
assumed for the footprint.
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Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
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6. Frequency reuse
Cellular system depends upon intelligent allocation and reuse
of channels.
Each BS is allocated separate group of channels to be used in
small geographic region called as CELL.
Adjacent cells are allocated separate group of channels.
BS antenna are designed to provide coverage to particular
cell.
By doing this same group of channels can be used again in
separate cells physically at large distance from cell containing
those channels by very well keeping interference within
tolerable limits.
This design process of selecting and allocating the channels of
CBS within system is called as frequency reuse.
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Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
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7. A cellular system which has a total of S duplex
channels.
S channels are divided among N cells, with each cell
uses unique and disjoint channels.
If each cell is allocated a group of k channels, then
S=kN.
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Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
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8. Terminology
• Cluster size : The N cells which collectively use the
complete set of available frequency is called the
cluster size.
• Co-channel cell : The set of cells using the same set
of frequencies as the target cell.
• Interference tier : A set of co-channel cells at the
same distance from the reference cell is called an
interference tier. The set of closest co-channel cells is
call the first tier. There is always 6 co-channel cells in
the first tier.
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Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
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9. Co-ordinates for hexagonal cellular geometry
• With these coordinates, an array of
cells can be laid out
so that the center of
every cell falls on a
point specified by a
pair of integer coordinates.
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Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
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11. Designing a cellular system
• N=19
• (i=3, j=2)
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Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
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12. Designing a cellular system
• The cluster size must satisfy: N = i2 + ij + j2
where i, j are non-negative integers.
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Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
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13. • Can also verify that
where Q is the co-channel reuse ratio
12/24/2013
Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
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14. Problem
•
•
Total 33 MHz b/w allocated to a FDD cellular system which uses 25 kHz simplex
channels to provide full duplex voice and control channels. Find the number of
channels available per cell if a system uses: a) four-cell reuse, b) 7-cell reuse. If 1
MHz of the allocated spectrum is dedicated to control channels, find an equitable
distribution of control channels & voice channels.
Total b/w = 33 MHz
–
–
•
For N=4,
–
•
•
Total no of ch per cell k = 660/7 = 95 channels
1MHz for control channels ie. 1000/50 = 20 control channels. So only 640 channels
(660-20) would be allotted for voice
For N = 4,
–
•
Total no of ch per cell k = 660/4 = 165 channels
For N = 7,
–
•
Channel b/w = 2 X 25khz = 50 khz
Total available channels S = 33, 000/50 = 660 channels
5 control ch + 160 voice ch per cell
For N =7,
–
–
4 cells with (3 control ch + 92 voice ch) & 2 cells with (3 control + 90 voice ch) & 1 cell with (2 control
ch + 92 voice channels)
Each cell with 1 control ch and 4 cells with 91 voice ch and 3 cells with 92 voice ch
15. Handover / Handoff
Occurs as a mobile moves into a different cell
during an existing call, or when going from
one cellular system into another.
It must be user transparent, successful and not
too frequent.
Not only involves identifying a new BS, but also
requires that the voice and control signals be
allocated to channels associated with the new BS.
12/24/2013
Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
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16. Once a particular signal level Pmin is specified as the
minimum usable signal for acceptable voice quality at the
BS receiver, a slightly stronger signal level PHO is used as
a threshold at which a handover is made.
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Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
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17. • =handoff threshold Minimum acceptable
signal to maintain the call
•
too small:
– Insufficient time
to complete handoff
before call is lost
– More call losses
•
too large:
– Too many handoffs
– Burden for MSC
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Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
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18. Dwell Time
The time over which a user remains within one cell is
called the dwell time.
The statistics of the dwell time are important for the
practical design of handover algorithms.
The statistics of the dwell time vary greatly,
depending on the speed of the user and the type of
radio coverage.
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Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
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19. Handover indicator
Each BS constantly monitors the signal strengths of all of
its reverse voice channels to determine the relative
location of each mobile user with respect to the BS. This
information is forwarded to the MSC who makes
decisions regarding handover.
Mobile assisted handover (MAHO) : The mobile station
measures the received power from surrounding BSs and
continually reports the results of these measurements to
the serving BS.
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Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
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20. Practical handover
• The Umbrella Cell approach
will help to solve this
problems. High speed users
are serviced by large
(macro) cells, while low
speed users are handled by
small (micro) cells.
21. Practical handover
• A hard handover does “break before make”,
ie. The old channel connection is broken
before the new allocated channel
connection is setup. This obviously can cause
call dropping.
• In soft handover, we do “make before break”,
ie. The new channel connection is
established before the old channel
connection is released. This is realized in
CDMA where also BS diversity is used to
improve boundary condition.
22. Interference and System Capacity
• In a given coverage area, there are several cells that use
the same set of frequencies. These cells are called cochannel cells. The interference between signals from
these cells is called co-channel interference.
• If all cells are approximately of the same size and the
path loss exponent is the same throughout the coverage
area, the transmit power of each BS is almost equal. We
can show that worse case signal to co-channel
interference is independent of the transmitted power. It
becomes a function of the cell radius R, and the distance
to the nearest co-channel cell D’.
• On control channel I/f leads to missed or block calls.
23. In urban areas more severe due high RF noise floor
The 2 major types are
Co-Channel interference
Adjacent channel interfernce
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24. Interference and System Capacity
Q- Co-Channel reuse ratio is given by:-
Let i0 is the no of co- channel nterfering cells than
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Dr.Vrince Vimal, MIT, MIET GROUP, MEERUT
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25. – Received power at a distance d from the
transmitting antenna is approximated by
– Useful signal at the cell boundary is the weakest,
given by Pr (R). Interference signal from the cochannel cell is given to be Pr (D′) .
26. Interference and System Capacity
– D’ is normally
approximated by
the base station
separation
between the two
cells D, unless
when accuracy is
needed. Hence
27. Interference and System Capacity
• For the forward link, a very general case,
where Di is the distance of the ith interfering
cell from the mobile, i0 is the total number of
co-channel cells exist.
28. Interference and System Capacity
• If only first tier co-channel cells are considered,
then i0 = 6.
Unless otherwise stated, normally assuming Di
≈ D for all i.
29. Outage probability
• The probability that a mobile station does not receive a
usable signal.
• For GSM, this is 12 dB and for AMPS, this is 18 dB. If
there is 6 co-channel cells, then
• Exercise : please verify this
– For n=4, a minimum cluster size of N=7 is needed to meet the
SIR requirements for AMPS.
– For n=4, a minimum cluster size of N=4 is required to meet the
SIR requirements for GSM
32. Outage probability
• More accurate SIR can be
obtained by computing the
actual distance.
• Our computation of outage
only based on path loss. For
more accurate
modeling, shadowing and fast
fading need to be taken into
consideration. This will not be
covered in this course.
33. •
Coverage Problems
Revision:
– Recall that the mean measured value,
– Measurement shows that at any value of d, the path loss PL(d)
at a particular location is random and distributed log-normally
(normal in dB) about this mean value.
Pr (d)dB = Pr (d)dB + Xσ
where Xσ is a zero-mean Gaussian distributed random variable
(in dB) with standard deviation σ(in dB).
34. Boundary coverage
• There will be a proportion of locations at distance R (cell radius) where a
terminal would experience a received signal above a threshold γ. (γ is
usually the receiver sensitivity)
• where Q(x) is the standard normal distribution.
35. Cell coverage
• Proportion of locations within the area defined by the cell
radius R, receiving a signal above the threshold γ.
37. Cell coverage
• Example: if n=4, σ=8 dB, and if the boundary is to have
75% coverage (75% of the time the signal is to exceed the
threshold at the boundary), then the area coverage is
equal to 94%.
• If n=2, σ=8 dB, and if the boundary is to have 75%
coverage, then the area coverage is equal to 91%.
• An operator needs to meet certain coverage criteria.
This is typically the “90% rule” – 90% of a given
geographical area must be covered for 90% of the time.
38. Cell coverage
• The mean signal level at any distance is determined by path
loss and the variance is determined by the resulting fading
distribution (log-normal shadowing, Rayleigh fading,
Nakagami-m, etc). In this course, we will deal with log-normal
shadowing only.
• The proportion of locations covered at a given distance (cell
boundary, for example) from BS can be found directly from
the resultant signal pdf/cdf.
• The proportion of locations covered within a circular region
defined by a radius R (the cell area, for example) can be found
by integrating the resultant cdf over the cell area.