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Fundamentals of Digital Communication by Upamanyu Madhow.pdf

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    Fundamental Digital Communication
    Half-title
    Copyright
    Contents
    Preface
    Organization
    How to use this book
    Acknowledgements
    CHAPTER 1 - Introduction
    1.1 Components of a digital communication system
    1.2 Text outline
    1.3 Further reading
    CHAPTER 2 - Modulation
    2.1 Preliminaries
    2.2 Complex baseband representation
    2.3 Spectral description of random processes
    2.3.1 Complex envelope for passband random processes
    2.4 Modulation degrees of freedom
    2.5 Linear modulation
    2.5.1 Examples of linear modulation
    2.5.2 Spectral occupancy of linearly modulated signals
    2.5.3 The Nyquist criterion: relating bandwidth to symbol rate
    2.5.4 Linear modulation as a building block
    2.6 Orthogonal and biorthogonal modulation
    2.7 Differential modulation
    2.8 Further reading
    2.9 Problems
    2.9.1 Signals and systems
    2.9.2 Complex baseband representation
    2.9.3 Random processes
    2.9.4 Modulation
    CHAPTER 3 - Demodulation
    3.1 Gaussian basics
    3.2 Hypothesis testing basics
    3.3 Signal space concepts
    3.4 Optimal reception in AWGN
    3.4.1 Geometry of the ML decision rule
    3.4.2 Soft decisions
    3.5 Performance analysis of ML reception
    3.5.1 Performance with binary signaling
    3.5.2 Performance with M-ary signaling
    3.6 Bit-level demodulation
    3.6.1 Bit-level soft decisions
    3.7 Elements of link budget analysis
    3.8 Further reading
    3.9 Problems
    3.9.1 Gaussian basics
    3.9.2 Hypothesis testing basics
    3.9.3 Receiver design and performance analysis for the AWGN channel
    3.9.4 Link budget analysis
    3.9.5 Some mathematical derivations
    CHAPTER 4 - Synchronization and noncoherent communication
    4.1 Receiver design requirements
    4.2 Parameter estimation basics
    4.2.1 Likelihood function of a signal in AWGN
    4.3 Parameter estimation for synchronization
    4.4 Noncoherent communication
    4.4.1 Composite hypothesis testing
    4.4.2 Optimal noncoherent demodulation
    4.4.3 Differential modulation and demodulation
    4.5 Performance of noncoherent communication
    4.5.1 Proper complex Gaussianity
    4.5.2 Performance of binary noncoherent communication
    4.5.3 Performance of M-ary noncoherent orthogonal signaling
    4.5.4 Performance of DPSK
    4.5.5 Block noncoherent demodulation
    4.6 Further reading
    4.7 Problems
    CHAPTER 5 - Channel equalization
    5.1 The channel model
    5.2 Receiver front end
    5.3 Eye diagrams
    5.4 Maximum likelihood sequence estimation
    5.4.1 Alternative MLSE formulation
    5.5 Geometric model for suboptimal equalizer design
    5.6 Linear equalization
    5.6.1 Adaptive implementations
    5.6.2 Performance analysis
    5.7 Decision feedback equalization
    5.7.1 Performance analysis
    5.8 Performance analysis of MLSE
    5.8.1 Union bound
    5.8.2 Transfer function bound
    5.9 Numerical comparison of equalization techniques
    5.10 Further reading
    5.11 Problems
    5.11.1 MLSE
    CHAPTER 6 - Information-theoretic limits and their computation
    6.1 Capacity of AWGN channel: modeling and geometry
    6.1.1 From continuous to discrete time
    6.1.2 Capacity of the discrete-time AWGN channel
    6.1.3 From discrete to continuous time
    6.1.4 Summarizing the discrete-time AWGN model
    6.2 Shannon theory basics
    6.2.1 Entropy, mutual information, and divergence
    6.2.2 The channel coding theorem
    6.3 Some capacity computations
    6.3.1 Capacity for standard constellations
    6.3.2 Parallel Gaussian channels and waterfilling
    6.4 Optimizing the input distribution
    6.4.1 Convex optimization
    6.4.2 Characterizing optimal input distributions
    6.4.3 Computing optimal input distributions
    6.5 Further reading
    6.6 Problems
    CHAPTER 7 - Channel coding
    7.1 Binary convolutional codes
    7.1.1 Nonrecursive nonsystematic encoding
    7.1.2 Recursive systematic encoding
    7.1.3 Maximum likelihood decoding
    7.1.4 Performance analysis of ML decoding
    7.1.5 Performance analysis for quantized observations
    7.2 Turbo codes and iterative decoding
    7.2.1 The BCJR algorithm: soft-in, soft-out decoding
    7.2.2 Logarithmic BCJR algorithm
    7.2.3 Turbo constructions from convolutional codes
    7.2.4 The BER performance of turbo codes
    7.2.5 Extrinsic information transfer charts
    7.2.6 Turbo weight enumeration
    7.3 Low density parity check codes
    7.3.1 Some terminology from coding theory
    7.3.2 Regular LDPC codes
    7.3.3 Irregular LDPC codes
    7.3.4 Message passing and density evolution
    7.3.5 Belief propagation
    7.3.6 Gaussian approximation
    7.4 Bandwidth-efficient coded modulation
    7.4.1 Bit interleaved coded modulation
    7.4.2 Trellis coded modulation
    7.5 Algebraic codes
    7.6 Further reading
    7.7 Problems
    CHAPTER 8 - Wireless communication
    8.1 Channel modeling
    8.2 Fading and diversity
    8.2.1 The problem with Rayleigh fading
    8.2.2 Diversity through coding and interleaving
    8.2.3 Receive diversity
    8.3 Orthogonal frequency division multiplexing
    8.4 Direct sequence spread spectrum
    8.4.1 The rake receiver
    8.4.2 Choice of spreading sequences
    8.4.3 Performance of conventional reception in CDMA systems
    8.4.4 Multiuser detection for DS-CDMA systems
    8.5 Frequency hop spread spectrum
    8.6 Continuous phase modulation
    8.6.1 Gaussian MSK
    8.6.2 Receiver design and Laurent’s expansion
    8.7 Space–time communication
    8.7.1 Space–time channel modeling
    8.7.2 Information-theoretic limits
    8.7.3 Spatial multiplexing
    8.7.4 Space–time coding
    8.7.5 Transmit beamforming
    8.8 Further reading
    8.9 Problems
    Appendix A - Probability, random variables, and random processes
    A.1 Basic probability
    A.2 Random variables
    A.3 Random processes
    A.3.1 Wide sense stationary random processes through LTI systems
    A.3.2 Discrete-time random processes
    A.4 Further reading
    Appendix B - The Chernoff bound
    Appendix C - Jensen’s inequality
    References
    Index
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    Fundamentals of Digital Communication This textbook presents the fundamental concepts underlying the design of modern digital communication systems, which include the wireline, wire- less, and storage systems that pervade our everyday lives. Using a highly accessible, lecture style exposition, this rigorous textbook first establishes a firm grounding in classical concepts of modulation and demodulation, and then builds on these to introduce advanced concepts in synchronization, non- coherent communication, channel equalization, information theory, channel coding, and wireless communication. This up-to-date textbook covers turbo and LDPC codes in sufficient detail and clarity to enable hands-on imple- mentation and performance evaluation, as well as “just enough” information theory to enable computation of performance benchmarks to compare them against. Other unique features include the use of complex baseband represen- tation as a unifying framework for transceiver design and implementation; wireless link design for a number of modulation formats, including space– time communication; geometric insights into noncoherent communication; and equalization. The presentation is self-contained, and the topics are selected so as to bring the reader to the cutting edge of digital communications research and development. Numerous examples are used to illustrate the key principles, with a view to allowing the reader to perform detailed computations and simulations based on the ideas presented in the text. With homework problems and numerous examples for each chapter, this textbook is suitable for advanced undergraduate and graduate students of electrical and computer engineering, and can be used as the basis for a one or two semester course in digital communication. It will also be a valuable resource for practitioners in the communications industry. Additional resources for this title, including instructor-only solutions, are available online at www.cambridge.org/9780521874144. Upamanyu Madhow is Professor of Electrical and Computer Engineering at the University of California, Santa Barbara. He received his Ph.D. in Electrical Engineering from the University of Illinois, Urbana-Champaign, in 1990, where he later served on the faculty. A Fellow of the IEEE, he worked for several years at Telcordia before moving to academia.
    Fundamentals of Digital Communication Upamanyu Madhow University of California, Santa Barbara
    CAMBRIDGE UNIVERSITY PRESS Cambridge, New York, Melbourne, Madrid, Cape Town, Singapore, São Paulo Cambridge University Press The Edinburgh Building, Cambridge CB2 8RU, UK Published in the United States of America by Cambridge University Press, New York www.cambridge.org Information on this title: www.cambridge.org/9780521874144 © Cambridge University Press 2008 This publication is in copyright. Subject to statutory exception and to the provision of relevant collective licensing agreements, no reproduction of any part may take place without the written permission of Cambridge University Press. First published in print format 2008 ISBN-13 978-0-511-38606-0 eBook (EBL) ISBN-13 978-0-521-87414-4 hardback Cambridge University Press has no responsibility for the persistence or accuracy of urls for external or third-party internet websites referred to in this publication, and does not guarantee that any content on such websites is, or will remain, accurate or appropriate.
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