Principles Of Communication Systems Simulation With .
Tranter FM revised 11-18.fm Page 1 Wednesday, November 19, 2003 10:34 AMPrinciplesof CommunicationSystems Simulationwith WirelessApplicationsWilliam H. TranterK. Sam ShanmuganTheodore S. RappaportKurt L. KosbarNOTAS IMPORTANTESAo longo do livro, as marcações come esta se referem aos tópicos de TP547 ministrados nas primeiras 40 horas do curso. Como elaspoderão ser atualizadas à medida que as aulas progredirem, recomenda-se refazer o download do correspondente arquivo PDF a cadasemana, por meio do link ula/27-easyfolder/42-tp547.Muitas das marcações supracitadas são apenas observações, outras são correções. Espera-se que a interpretação das versões incorretas(ou parcialmente corretas) e corretas possa contribuir ainda mais para o entendimento dos conceitos, já que as incorreções sãoexemplos de falhas de interpretação comuns por parte dos alunos.PRENTICE HALLOs assuntos cobertos pelo curso têm como pré-requisito as disciplinas TP537 (Transmissão Digital) e TP501 ística e Processes Estocásticos), e como co-requisitoa disciplinaTP519 (Análisede Desempenho de Redes deUpper SaddleRiver, NewdeJerseyTelecomunicações). Pressupõe-se também o conhecimentosobre fundamentosSinais e07458Sistemas Lineares e de MATLAB.www.phptr.comEste livro, embora não vá ser utilizado em sua totalidade, tem um conteúdo bastante abrangente e direcionado para sistemas decomunicação, sendo portanto muito útil como fonte de consulta para a modelagem, o desenvolvimento e a implementação desimulações. Como complemento, principalmente no que se refere à simulação de sistemas contínuos, o livro Digital Transmission - ASimulation-Aided Introduction with VisSim/Comm, de autoria do Prof. Dayan Adionel Guimarães, também poderá ser útil. Nasanotações aqui registradas tal livro é referido como Digital Transmission.Por fim, os códigos em MATLAB apresentados no livro, alguns com versões complementadas ou corrigidas na pasta de TP547 napágina https://www.inatel.br/docentes/dayan/, não serão alvo de explicações detalhadas por parte do professor, pois vale lembrar queo curso é sobre princípios de simulação, não sobre MATLAB.
Tranter FM revised 11-18.fm Page 2 Wednesday, November 19, 2003 10:34 AMLibrary of Congress Cataloging-in-Publication DataPrinciples of communication systems simulation with wireless applications / William H. Tranter .[et al.]p. cm. – (Prentice Hall communications engineering and emerging technologies series ; 16)Includes bibliographical references and index.ISBN 0-13-494790-81. Telecommunication systems–Computer simulation. I. Tranter, William H. II. Series.TK\5102.5.P673 ion supervision: Kerry ReardonComposition: Lori Hughes and TIPS Technical Publishing, Inc.Cover design director: Jerry VottaCover design: Nina ScuderiArt director: Gail Cocker-BoguszManufacturing manager: Alexis Heydt-LongManufacturing buyer: Maura ZaldivarPublisher: Bernard GoodwinEditorial assistant: Michelle VincentiMarketing manager: Dan DePasqualeFull-service production manager: Anne R. GarciaCopyright 2004 Pearson Education, Inc.Prentice Hall Professional Technical ReferenceUpper Saddle River, NJ 07458Prentice Hall PTR offers excellent discounts on this book when ordered in quantity for bulk purchases of specialsales. For more information, please contact: U.S. Corporate and Government Sales, 1-800-382-3419,corpsales@pearsontechgroup.com. For sales outside of the U.S., please contact: International Sales, 1-317-5813793, international@pearsontechgroup.comCompany and product names mentioned herein are the trademarks of their respective owners.MATLAB is a registered trademark of The MathWorks, Inc. for MATLAB product information, please contact:The Mathworks, Inc.3 Apple Hill DriveNatick, MA 01760-2098 USATel: 508-647-7000Fax: 508-647-7101Email: info@mathworks.comWeb: www.mathworks.comAll rights reserved. No part of this book may be reproduced, in any form or by any means, without permission inwriting from the publisher.Printed in the United States of AmericaFirst printingISBN 0-13-494790-8Pearson Education LTD.Pearson Education Australia PTY, LimitedPearson Education Singapore, Pte. Ltd.Pearson Education North Asia Ltd.Pearson Education Canada, Ltd.Pearson Education de Mexico, S.A. de C.V.Pearson Education-JapanPearson Education Malaysia, Pte. Ltd.
Tranter FM revised 11-18.fm Page 3 Wednesday, November 19, 2003 10:34 AM
Tranter FM revised 11-18.fm Page 4 Wednesday, November 19, 2003 10:34 AMDedicationsTo my loving and supportive wife Judy.William H. TranterTo my loving wife Radha.K. Sam ShanmuganTo my loving wife, our children, and my former students.Theodore S. RappaportTo my wife and children.Kurt L. Kosbar
ii“TranterBook” — 2003/11/18 — 14:44 — page v — #1iiCONTENTSPREFACExviiTópico doplano de ensinoPart IIntroduçãoIntroduction1 THE ROLE OF SIMULATION1.1Examples of Complexity1.1.1The Analytically Tractable System1.1.2The Analytically Tedious System1.1.3The Analytically Intractable System1.2Multidisciplinary Aspects of Simulation1.3Models1.4Deterministic and Stochastic Simulations1.4.1An Example of a Deterministic Simulation1.4.2An Example of a Stochastic Simulation1.5The Role of Simulation1.5.1Link Budget and System-Level Specification Process1.5.2Implementation and Testing of Key Components1.5.3Completion of the Hardware Prototype and Validationof the Simulation Model1.5.4End-of-Life Predictions1.6Software Packages for Simulation1.7A Word of Warning1.8The Use of MATLAB1.9Outline of the Book1.10 Further Reading11235781114161719202222222326272728viiii
ii“TranterBook” — 2003/11/18 — 14:44 — page vi — #2iviFundamentosFundamentosiContents2 SIMULATION METHODOLOGY2.1Introduction2.2Aspects of Methodology2.2.1Mapping a Problem into a Simulation Model2.2.2Modeling of Individual Blocks2.2.3Random Process Modeling and Simulation2.3Performance Estimation2.4Summary2.5Further Reading2.6Problems31323434414749525252Part II55Fundamental Concepts and Techniques3 SAMPLING AND QUANTIZING3.1Sampling3.1.1The Lowpass Sampling Theorem3.1.2Sampling Lowpass Random Signals3.1.3Bandpass Sampling3.2Quantizing3.3Reconstruction and Interpolation3.3.1Ideal Reconstruction3.3.2Upsampling and Downsampling3.4The Simulation Sampling Frequency3.4.1General Development3.4.2Independent Data Symbols3.4.3Simulation Sampling Frequency3.5Summary3.6Further Reading3.7References3.8Problems4 LOWPASS SIMULATION MODELS FOR BANDPASSSIGNALS AND SYSTEMS4.1The Lowpass Complex Envelope for Bandpass Signals4.1.1The Complex Envelope: The Time-Domain View4.1.2The Complex Envelope: The Frequency-Domain View )4.1.3Derivation of Xd (f ) and Xq (f ) from X(f4.1.4Energy and 0111iiii
ii“TranterBook” — 2003/11/18 — 14:44 — page vii — adrature Models for Random Bandpass Signals4.1.6Signal-to-Noise RatiosLinear Bandpass Systems4.2.1Linear Time-Invariant Systems4.2.2Derivation of hd (t) and hq (t) from H(f )Multicarrier SignalsNonlinear and Time-Varying Systems4.4.1Nonlinear Systems4.4.2Time-Varying SystemsSummaryFurther ReadingReferencesProblemsAppendix A: MATLAB Program QAMDEMO4.9.1Main Program: c4 qamdemo.m4.9.2Supporting RoutinesAppendix B: Proof of Input-Output Relationship5 FILTER MODELS AND SIMULATION TECHNIQUES5.1Introduction5.2IIR and FIR Filters5.2.1IIR Filters5.2.2FIR Filters5.2.3Synthesis and Simulation5.3IIR and FIR Filter Implementations5.3.1Direct Form II and Transposed DirectForm II Implementations5.3.2FIR Filter Implementation5.4IIR Filters: Synthesis Techniques and Filter Characteristics5.4.1Impulse-Invariant Filters5.4.2Step-Invariant Filters5.4.3Bilinear z-Transform Filters5.4.4Computer-Aided Design of IIR Digital Filters5.4.5Error Sources in IIR Filters5.5FIR Filters: Synthesis Techniques and Filter Characteristics5.5.1Design from the Amplitude Response5.5.2Design from the Impulse Response5.5.3Implementation of FIR Filter Simulation Models5.5.4Computer-Aided Design of FIR Digital 167167170177180184iiii
ii“TranterBook” — 2003/11/18 — 14:44 — page viii — nts on FIR DesignSummaryFurther ReadingReferencesProblemsAppendix A: Raised Cosine Pulse Example5.10.1 Main program c5 rcosdemo.m5.10.2 Function file c5 rcos.mAppendix B: Square Root Raised Cosine Pulse Example5.11.1 Main Program c5 sqrcdemo.m5.11.2 Function file c5 sqrc.mAppendix C: MATLAB Code and Data for Example 5.115.12.1 c5 FIRFilterExample.m5.12.2 FIR Filter AMP Delay.m5.12.3 shift ifft.m5.12.4 log psd.m6 CASE STUDY: PHASE-LOCKED LOOPSAND DIFFERENTIAL EQUATION METHODS6.1Basic Phase-Locked Loop Concepts6.1.1PLL Models6.1.2The Nonlinear Phase Model6.1.3Nonlinear Model with Complex Input6.1.4The Linear Model and the Loop Transfer Function6.2First-Order and Second-Order Loops6.2.1The First-Order PLL6.2.2The Second-Order PLL6.3Case Study: Simulating the PLL6.3.1The Simulation Architecture6.3.2The Simulation6.3.3Simulation Results6.3.4Error Sources in the Simulation6.4Solving Differential Equations Using Simulation6.4.1Simulation Diagrams6.4.2The PLL Revisited6.5Summary6.6Further 210214215215216219220223224225230231231232iiii
ii“TranterBook” — 2003/11/18 — 14:44 — page ix — #5iixContents6.96.106.116.12Geração denúmerosaleatóriosiAppendix A: PLL Simulation ProgramAppendix B: Preprocessor for PLL Example SimulationAppendix C: PLL Postprocessor6.11.1 Main Program6.11.2 Called RoutinesAppendix D: MATLAB Code for Example 6.37 GENERATING AND PROCESSING RANDOM SIGNALS7.1Stationary and Ergodic Processes7.2Uniform Random Number Generators7.2.1Linear Congruence7.2.2Testing Random Number Generators7.2.3Minimum Standards7.2.4MATLAB Implementation7.2.5Seed Numbers and Vectors7.3Mapping Uniform RVs to an Arbitrary pdf7.3.1The Inverse Transform Method7.3.2The Histogram Method7.3.3Rejection Methods7.4Generating Uncorrelated Gaussian Random Numbers7.4.1The Sum of Uniforms Method7.4.2Mapping a Rayleigh RV to a Gaussian RV7.4.3The Polar Method7.4.4MATLAB Implementation7.5Generating Correlated Gaussian Random Numbers7.5.1Establishing a Given Correlation Coefficient7.5.2Establishing an Arbitrary PSDor Autocorrelation Function7.6Establishing a pdf and a PSD7.7PN Sequence Generators7.8Signal Processing7.8.1Input/Output Means7.8.2Input/Output Cross-Correlation7.8.3Output Autocorrelation Function7.8.4Input/Output Variances7.9Summary7.10 Further Reading7.11 References7.12 1292293293294294295iiii
ii“TranterBook” — 2003/11/18 — 14:44 — page x — #6ixContents7.137.14Estudo eletivo:processamento desinais aleatórios,somente Seção 8.2Métodos deMonte CarloiAppendix A: MATLAB Code for Example 7.11Main Program: c7 Jakes.m7.14.1 Supporting Routines2992993008 POSTPROCESSING8.1Basic Graphical Techniques8.1.1A System Example—π/4 DQPSK Transmission8.1.2Waveforms, Eye Diagrams, and Scatter Plots8.2Estimation8.2.1Histograms8.2.2Power Spectral Density Estimation8.2.3Gain, Delay, and Signal-to-Noise Ratios8.3Coding8.3.1Analytic Approach to Block Coding8.3.2Analytic Approach to Convolutional Coding8.4Summary8.5Further Reading8.6References8.7Problems8.8Appendix A: MATLAB Code for Example 8.18.8.1Main Program: c8 pi4demo.m8.8.2Supporting 3393423423449 INTRODUCTION TO MONTE CARLO METHODS9.1Fundamental Concepts9.1.1Relative Frequency9.1.2Unbiased and Consistent Estimators9.1.3Monte Carlo Estimation9.1.4The Estimation of π9.2Application to Communications Systems—The AWGN Channel9.2.1The Binomial Distribution9.2.2Two Simple Monte Carlo Simulations9.3Monte Carlo Integration9.3.1Basic Concepts9.3.2Convergence9.3.3Confidence Intervals9.4Summary9.5Further 54355359366368370371375375375376iiii
ii“TranterBook” — 2003/11/18 — 14:44 — page xi — #7iContents10 MONTE CARLO SIMULATIONEstudo eletivo:OF COMMUNICATION SYSTEMSexemplos adicionais de10.1 Two Monte Carlo Examplesaplicação do métodode Monte Carlo10.2 Semianalytic Techniques10.2.1 Basic Considerations10.2.2 Equivalent Noise Sources10.2.3 Semianalytic BER Estimation for PSK10.2.4 Semianalytic BER Estimation for QPSK10.2.5 Choice of Data Sequence10.3 Summary10.4 References10.5 Problems10.6 Appendix A: Simulation Code for Example 10.110.6.1 Main Program10.6.2 Supporting Program: random binary.m10.7 Appendix B: Simulation Code for Example 10.210.7.1 Main Program10.7.2 Supporting Programs10.7.3 vxcorr.m10.8 Appendix C: Simulation Code for Example 10.310.8.1 Main Program: c10 PSKSA.m10.8.2 Supporting Programs10.9 Appendix D: Simulation Code for Example 10.410.9.1 Supporting Programs11 METHODOLOGY FOR SIMULATINGA WIRELESS SYSTEM11.1 System-Level Simplifications and Sampling Rate Considerations11.2 Overall Methodology11.2.1 Methodology for Simulation of the Analog Portionof the System11.2.2 Summary of Methodology for Simulatingthe Analog Portion of the System11.2.3 Estimation of the Coded BER11.2.4 Estimation of Voice-Quality Metric11.2.5 Summary of Overall Methodology11.3 Summary11.4 Further Reading11.5 References11.6 1442443443444444iiii
ii“TranterBook” — 2003/11/18 — 14:44 — page xii — #8ixiiPart IIIModelagem esimulação denão-linearidades.Tópico eletivo:Seção 12.3iContentsAdvanced Models and Simulation Techniques12 MODELING AND SIMULATION OF NONLINEARITIES12.1 Introduction12.1.1 Types of Nonlinearities and Models12.1.2 Simulation of Nonlinearities—Factors to Consider12.2 Modeling and Simulation of Memoryless Nonlinearities12.2.1 Baseband Nonlinearities12.2.2 Bandpass Nonlinearities—Zonal Bandpass Model12.2.3 Lowpass Complex Envelope(AM-to-AM and AM-to-PM) Models12.2.4 Simulation of Complex Envelope Models12.2.5 The Multicarrier Case12.3 Modeling and Simulation of Nonlinearities with Memory12.3.1 Empirical Models Based on Swept Tone Measurements12.3.2 Other Models12.4 Techniques for Solving Nonlinear Differential Equations12.4.1 State Vector Form of the NLDE12.4.2 Recursive Solutions of NLDE-Scalar Case12.4.3 General Form of Multistep Methods12.4.4 Accuracy and Stability of Numerical Integration Methods12.4.5 Solution of Higher-Order NLDE-Vector Case12.5 PLL Example12.5.1 Integration Methods12.6 Summary12.7 Further Reading12.8 References12.9 Problems12.10 Appendix A: Saleh’s Model12.11 Appendix B: MATLAB Code for Example 12.212.11.1 Supporting Routines13 MODELING AND SIMULATIONOF TIME-VARYING SYSTEMS13.1 Introduction13.1.1 Examples of Time-Varying Systems13.1.2 Modeling and Simulation Approach13.2 Models for LTV Systems13.2.1 Time-Domain Description for LTV 98499500500iiii
ii“TranterBook” — 2003/11/18 — 14:44 — page xiii — #9iContents13.2.2 Frequency Domain Description of LTV Systems13.2.3 Properties of LTV Systems13.3 Random Process Models13.4 Simulation Models for LTV Systems13.4.1 Tapped Delay Line Model13.5 MATLAB Examples13.5.1 MATLAB Example 113.5.2 MATLAB Example 213.6 Summary13.7 Further Reading13.8 References13.9 Problems13.10 Appendix A: Code for MATLAB Example 113.10.1 Supporting Program13.11 Appendix B: Code for MATLAB Example 213.11.1 Supporting Routines13.11.2 mpsk pulses.mEstudo eletivo:aplicações desimulação desistemas contínuos14 MODELING AND SIMULATIONOF WAVEFORM CHANNELS14.1 Introduction14.1.1 Models of Communication Channels14.1.2 Simulation of Communication Channels14.1.3 Discrete Channel Models14.1.4 Methodology for Simulating CommunicationSystem Performance14.1.5 Outline of Chapter14.2 Wired and Guided Wave Channels14.3 Radio Channels14.3.1 Tropospheric Channel14.3.2 Rain Effects on Radio Channels14.4 Multipath Fading Channels14.4.1 Introduction14.4.2 Example of a Multipath Fading Channel14.4.3 Discrete Versus Diffused Multipath14.5 Modeling Multipath Fading Channels14.6 Random Process Models14.6.1 Models for Temporal Variationsin the Channel Response 538538545546547549iiii
ii“TranterBook” — 2003/11/18 — 14:44 — page xiv — .6.2 Important ParametersSimulation Methodology14.7.1 Simulation of Diffused Multipath Fading Channels14.7.2 Simulation of Discrete Multipath Fading Channels14.7.3 Examples of Discrete Multipath Fading Channel Models14.7.4 Models for Indoor Wireless ChannelsSummaryFurther ReadingReferencesProblemsAppendix A: MATLAB Code for Example 14.114.12.1 Main Program14.12.2 Supporting FunctionsAppendix B: MATLAB Code for Example 14.214.13.1 Main Program14.13.2 Supporting Functions15 DISCRETE CHANNEL MODELS15.1 Introduction15.2 Discrete Memoryless Channel Models15.3 Markov Models for Discrete Channels with Memory15.3.1 Two-State Model15.3.2 N -state Markov Model15.3.3 First-Order Markov Process15.3.4 Stationarity15.3.5 Simulation of the Markov Model15.4 Example HMMs—Gilbert and Fritchman Models15.5 Estimation of Markov Model Parameters15.5.1 Scaling15.5.2 Convergence and Stopping Criteria15.5.3 Block Equivalent Markov Models15.6 Two Examples15.7 Summary15.8 Further Reading15.9 References15.10 Problems15.11 Appendix A: Error Vector Generation15.11.1 Program: c15 errvector.m15.11.2 Program: c15 15621622622623627627628iiii
ii“TranterBook” — 2003/11/18 — 14:44 — page xv — #11ixvContents15.1215.1315.1415.15iAppendix B: The Baum-Welch AlgorithmAppendix C: The Semi-Hidden Markov ModelAppendix D: Run-Length Code GenerationAppendix E: Determination of Error-Free Distribution15.15.1 c15 intervals1.m15.15.2 c15 intervals2.m62963263663763763716 EFFICIENT SIMULATION TECHNIQUES16.1 Tail Extrapolation16.2 pdf Estimators16.3 Importance Sampling16.3.1 Area of an Ellipse16.3.2 Sensitivity to the pdf16.3.3 A Final Twist16.3.4 The Communication Problem16.3.5 Conventional and Improved Importance Sampling16.4 Summary16.5 Further Reading16.6 References16.7 Problems16.8 Appendix A: MATLAB Code for Example 16.316.8.1 Supporting 66917 CASE STUDY: SIMULATIONOF A CELLULAR RADIO SYSTEM17.1 Introduction17.2 Cellular Radio System17.2.1 System-Level Description17.2.2 Modeling a Cellular Communication System17.3 Simulation Methodology17.3.1 The Simulation17.3.2 Processing the Simulation Results17.4 Summary17.5 Further Reading17.6 References17.7 Problems17.8 Appendix A: Program for Generating the Erlang B Chart17.9 Appendix B: Initialization Code for Simulation17.10 Appendix C: Modeling Co-Channel 0712714iiii
ii“TranterBook” — 2003/11/18 — 14:44 — page xvi — #12ixvi17.10.1 Wilkinson’s Method17.10.2 Schwartz and Yeh’s Method17.11 Appendix D: MATLAB Code for Wilkinson’s MethodiContents71571771818 TWO EXAMPLE SIMULATIONS18.1 A Code-Division Multiple Access System18.1.1 The System18.1.2 The Simulation Program18.1.3 Example Simulations18.1.4 Development of Markov Models18.2 FDM System with a Nonlinear Satellite Transponder18.2.1 System Description and Simulation Objectives18.2.2 The Overall Simulation Model18.2.3 Uplink FDM Signal Generation18.2.4 Satellite Transponder Model18.2.5 Receiver Model and Semianalytic BER Estimator18.2.6 Simulation Results18.2.7 Summary and Conclusions18.3 References18.4 Appendix A: MATLAB Code for CDMA Example18.4.1 Supporting Functions18.5 Appendix B: Preprocessors for CDMA Application18.5.1 Validation Run18.5.2 Study Illustrating the Effect of the Ricean K-Factor18.6
1.2 Multidisciplinary Aspects of Simulation 8 1.3 Models 11 1.4 Deterministic and Stochastic Simulations 14 1.4.1 An Example of a Deterministic Simulation 16 1.4.2 An Example of a Stochastic Simulation 17 1.5 The Role of Simulation 19 1.5.1 Link Budget and System-Level Specification Process 20 1.5.2 Implementation and Testing of Key Components 22
systems, both analytic and simulation, to guide the analysis and design throughout the life cycle of a system. Computer-aided design, analysis, and simulation of communication systems constitute a new and important part of this process. This thesis studies different aspects of the simulation of communication systems by covering
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Solutions Manual Discrete-Event System Simulation Fourth Edition Jerry Banks John S. Carson II Barry L. Nelson David M. Nicol January 4, 2005. Contents 1 Introduction to Simulation 1 2 Simulation Examples 5 3 General Principles 19 4 Simulation Software 20 5 Statistical Models in Simulation 21 6 Queueing Models 36 7 Random-Number Generation 44 8 .
What Is Mass Communication? Cultural definition of communication (1975)! James W. Carey: “Communication is a symbolic process whereby reality is produced, maintained, repaired and transformed.”! Carey’s updated definition (1989) asserts that communication and reality are linked. It’s truest purpose is to maintain ever-evolving,File Size: 1MBPage Count: 22Explore furtherIntroduction to Mass Communication: Media Literacy and .www.researchgate.netDownload [PDF] Introduction To Mass Communication eBookardhindie.comIntroduction To Mass Communication 7th Editionicomps.com(PDF) Media And Culture - An Introduction To Mass .www.academia.eduIntroduction to mass communication - Archivearchive.orgRecommended to you b
The Simulation Security of SCADA Systems Simulation of SCADA Systems Simulation of SCADA Systems It is essential to model and simulate communication networks to study mission critical situations SCADA system is composed of units in domains like dynamic systems, networks and physical environments Each of these units can be modeled using a variety of
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