Preface 1 Introduction 1-1 Elements of a Digital Communication System 1-2 Communication Channels and Their Characteristics 1-3 Mathematical Models for Communication Channels 1-4 A Historical Perspective in the Development of Digital Communications 1-5 Overview of the Book 2 Probability and Stochastic Processes 2-1 Probability 2-1-1 Random Variables,Probability Distributions,and Probablity Densities 2-1-2 Functions of Random Variables 2-1-3 Statistical Averages of Random Variables 2-1-4 Some Useful Probability Distributions 2-1-5 Upper bounds on the Tail Probability 2-1-6 Sums of Random Variables and the Central Limit Theorem 2-2 Stochastic Processes 2-2-1 Statistical Avergaes 2-2-2 Power Density Spectrum 2-2-3 Response of a Linesr Time -Invariant System to a Random input Signal 2-2-4 Samppling Theorem for Band -Linmited Stochastic Processes 2-2-5 Discrete -Time Stochastic Signals and Systems 2-2-6 Cyclostationary Processes 2-3 Bibliographical Notes and References Problems 3 Source Clding 3-1 Mathematical Models for Information 3-2 A Logarithmic Measurd of Information 3-2-1 Average Mutual Information and Entropy 3-2-2 Information Measures for Continuous Random Variables 3-3 Coding for Discrete Sources 3-3-1 Coding for Discrete Memoryless Sources 3-3-2 Discrete Stationary Sources 3-3-3 The Lemple-Ziv Alogrithm 3-4 Coding for Analog Sources -Optimum Quantization 3-4-1 Rate -Distortion Function 3-4-2 Scalar Quantization 3-4-3 Vector Quantixation 3-5 Coding Techniques for Analog Sources 3-5-1 Temporal Waveform Coding 3-5-2 Spectral Waveform Coding 3-5-3 Model -Based Source Coding 3-6 Bibliographical Notes and References Problems 4 Characterization of Communication Signals and Systems 4-1 Representation of Bandpass Signals and Systems 4-1-1 Representation of Bandpass Signals 4-1-2 Representation of Linear Bandpass Systems 4-1-3 Response of a Bandpass System to a Bandpass Signal 4-1-4 Representation of Bandpass Staionary Stochastic Processes 4-2 Signal Space Representation 4-2-1 Vector Space Concepts 4-2-2 Signal Space Concepts 4-2-3 Orthogonal Expansions of Singnals 4-3 Representation of Digitally Modulated Signals 4-3-1 memory less modulation Methods 4-3-2 Linear Modulation with Memory 4-3-3 Nonlinear Modulation Methods with Memory 4-4 Spectral Characteristics of Digitally Modulated Signals 4-4-1 Power Spectra of Linearly Mldulated Siognals 4-4-2 Power Spectra of CPFSK and CPM Signals 4-4-3 Power Spectra of Modulated Signals with memory 4-5 Bibliographical Notes and References Problems 5 Optimum Receivers for the Additive White Gaussian Noise Channel 5-1 Optimum Receiver for Signals Corrupted by AWGN 5-1-1 Correlation Demodulator 5-1-2 Matched -Filter Demodulator 5-1-3 The Optimum Detector 5-1-4 The Maximum-Likelihood Sequence Detector 5-1-5 A Symblo-by-Symbol MAP Detector for Signals with Memory 5-2 Performance of the Optimum Receiver for Memoryles Modulation 5-2-1 Probability of Error for Binary Dodulation 5-2-2 Probability of Error for M-ary Orthogonal Signals 5-2-3 Probability of Error for M-ary Biorthogonal Signals 5-2-4 Probability of Error for M-ary Simples Signals 5-2-5 Probability of Error for M-ary Binary-Coded signals 5-2-6 Probability of Error for M-ary PAM 5-2-7 Probability of Error for M-ary PSK 5-2-8 Differential PSK (DPSK) and its Performance 5-2-9 Probability of Error for QAM 5-2-10 Comparison of Digital Modulation Methods 5-3 Optimum Receiver for Cpm Signals 5-3-1 Optimum demodulation an dDetection of CPM 5-3-2 Performance of CPM Signals 5-3-3 Symbol -by*Symbol detection of CPM Signals 5-4 Optimum Receiver for Signals with Random Phase in AWGN Channel 5-4-1 Optimum Demodulation an dDetection of Signals 5-4-2 Optimum Receiver for M-ary Orthogonal Signals 5-4-3 Probability of Error for envelope Detection of M-aary Orthogonal Signals 5-4-4 Probability of Error Envelope Dtection of Correlated Binary Signals 5-5 Regenerative Repeaters and Link Budget Analysis 5-5-1 Regenerative Repeaters 5-5-2 communication Link Budget Anylysis 5-6 Bibliographical Notes and References Problems 6 Crrier and Symbol Synchronization 6-1 Signal Parameter Estimation 6-1-1 The Like lihood function 6-1-2 Carrier Recovery and Symbol Synchronization in Signal Demodulation 6-2 Signal Parameter Estimation 6-1-2 Carrier Recovery and Symbol Synchronization in signal Demodulation 6-2 Carrier Phase Estimation 6-2-1 Maximim-Likelihood Carrier Phase Estimation 6-2-2 The Phase -Locked Loop 6-2-3 Effect of Additive Noise on th ePhase Estimate 6-2-4 Decision-Diredted Loops 6-2-5 Non-Decision -Directed Loops 6-3 Symbol Timing Estimation 6-3-1 Maximum -Lilelihood Timing Estimation 6-3-2 Non-Decision-Directed Timing Estimation 6-4 Joint Estimation of Carrier Phase and Symbol Timing 6-5 Performance Characterisitics of ML Estimators 6-6 Bibliographical Notes and References Problems 7 Channel Capacity and Coding 7-1 Channel Models and Channel Capacity 7-1-1 Channel Models 7-1-2 Channel Capacity 7-1-3 Achieving Channel Capacity with Orthogonal Signals 7-1-4 Channel rliability Functions 7-2 Random Selection of Codes 7-2-1 Random Coding Based on M-ary binary -Coded Sjignals 7-2-2 Rjandom Coding Based on M-ary Multiamplitude Signals 7-2-3 Comparison of Ro with the Capacity of th eAWGN channel 7-3 Communication System Design Based on the Cutoff Rate 7-4 Bibliographical Notes and References Problems 8 Block and Convllutional Channel Codes 8-1 Linear Block Codes 8-1-1 The Generator Matrix and the Parity Check Matrix 8-1-2 Some Specific Linear Block Cldes 8-1-3 Cyclic Cldes 8-1-4 Optimum Sjoft-Decision Decoding of Linear Block Codes 8-1-5 Hard -Decision Decoding 8-1-7 Bounds on Minimum distance of Linear Block Codes 8-1-8 Nonbinary Block Cjodes and Concatenated Block Codes 8-1-9 Interleaving of Coded Data for Channels with Burst Errors 8-2 Convolutional Codes 8-2-1 The Transfer Function of a Convolutional Code 8-2-2 Optimum Decoding of Cjonvolutional Codes-The Viterbi Algorithm 8-2-3 Probability of Error for Soft-Decision Decoding 8-2-4 Probability of Error Hard-Decision Decoding 8-2-5 Distance Properties of Binary Convolutional Codes 8-2-6 Nonbinary Dual-k Codes and Concatenated Codes 8-2-7 Other Decoding Alogorithms for Convolutional Codes Convolutional Codes 8-3 Coded Modulation fro Bandwidth-Constrained Channels 8-4 Bibliographical Notes and References Problems 9 Signal Design for Band-Limtited Channels 9-1 Characterization of Band-Limited Channels 9-2 Signal Design for Band -Limited Channels 9-2- l Design for Band -Limited Signals for No Intersymbol Interference-The Nyquist Criterion 9-2-2 Design of Band--Limited Signals with Cjontrolled ISI-Partial -Response Signal 9-2-3 Data Detection for controlled ISI 9-2-4 Signal Design for Channels with Distortion 9-3 Probability of Error in Detection of PAM 9-3-1 Probibilty of Error for Detection of PAM with Zero ISI 9-3-2 Probibilty of Error for Detection of Partial -Response Signals 9-3-3 Probability of Error for Optimum Signals in Channel with Distortion 9-4 Modulation codes for Sjpectrum Shaping 9-5 Bibliographical Notes and References 10 Communication through Band-Limited Linear Filter Channels 10-1 Optimum Receiver for Channels with ISI an dAWGN 10-1-1 Optimum Maximum-Likelihood Receiver 10-1-2 A Discrete -time Model for a Channel with ISI 10-1-3 The Viterbi Alorithm for the Discrete -Time White Noise Filter Model 10-1-4 Performance of MLSE for Channels with ISI 10-2 Linear Equalization 10-2-1 Peak Distortion Criterion 10-2-2 Mean Square Error(MSE) Criterion 10-2-3 Performance Characteristics of th MSE Equalizer 10-2-4 Fractionally Spaced Equalizer 10-3 Decision -Feedback Equalization 10-3-1 Coefficient Optimization 10-3-2 Performance Characteristics of DFE 10-3-3 Predictive Decision-Feedback Equalize Problems 11 Adaptive Equalization 11-1 Adaptive Linear Equalizer 11-1-1 The Zero -Rorcing Algorithm 11-1-2 The LMX algorithm 11-1-3 Convergence Properties of the LMS Algorithm 11-1-4 Excess MSE Due to Noisy Gradient Estimates 11-1-5 Baseband and Passband Linear EQualizers 11-2 Adaptive Decision-Feedback Equalizer 11-2-1 Adaptive Quqlization of Trellis -Coded Signals 11-3 An Adaptive Channel Estimator for ML Sequence Detection 11-4 Recusive Least -Squares Alogrithms for Adaptive Equalization 11-4-1 Recursive Least-Squares(Kalman )Alogorithm 11-4-2 Linear Prediction an dthe Lattice Filter 11-5 Self -Recovering(Blind) Equalization 11-5-1 Blind Equalization Based on Maxmum-Likelihood Criterion 11-5-2 Stochastic Gradient Alogorithms 11-5-3 Blind Equalization Algorithms Based on Second-and Higher-Order Signal Statistics 11-6 Bibliographical Notes and Referencs Prlblems 12 Multichannel and Multicarrier Systems 12-1 Multichannel Digital Communication in AWGN Channels 12-1-1 Binary Signals 12-1-2 M-ary Orthogonal Signals 12-3 Bibiliographical Notes and References Problems 13 Spread Sjpectrum Signals for Digital Communications 13-1 Model of Spread Spectrum Digital Communication System 13-2 Direct Sequence Spread Spectrum Signals 13-2-1 Error Rate Performance of the Decoder 13-2-2 Some Applications of DS Spread Spectrum Signals 13-2-3 Effect of Pulsed Interference on DS Spread Sjpecturm Systems 13-2-4 Generation of PN Sequences 13-3 Frequency -Hoppped Spread Spectrum Signals 13-3-1 Performance of FH Spread Spectrum Signals in AWGN Channel 13-3-2 Performance of FH Spead Speftrum Signals in Partial-Band Interference 13-3-3 A CDMA System Based on FH Spread Spectrum Signals 13-4 Other Types of Sjpead Spectrum Signals 13-5 Synchronization of Spead Spectrum Signals 13-6 Bibliographical Notes and References Problems 14 Digital Communication thjrough Fading Multipath Channels 14-1 Charatcterization of Fading Multipath Channels 14-1-1 Channel Correlation Functions and Power Spectra 14-1-2 Statistical Models ofr Fading Channels 14--3 The Effect of Characteristics on the Choice of a Channel Model 14--4 Frequency -Nonselective,Slowly Fading Channel 14-4-1 Binary Signals 14-4-2 Multiphase Sinals 14-4-3 M-ary Orthogonal Signals 14-5 Digital Signaling over a Frequency-Selective,Slowly Fading Channel 14-5-1 A Tapped-Delay -Line Channel Model 14-5-2 The RAKE Demodulator 14-5-3 Performance of RAKEm Receiver 14-6 Coded Wavefrms for Fading Channels 14-6-1 Probability of Error for Soft-Decistion Decoding of Liear Binary Block Codes 14-6-2 Probility of Error for Jard-Decision Dcoding of Linear Binary Block Codes 14-6-3 Upper Bound on the Performance of Convolutional Codes for a Raleigh Fading Channel 14-6-4 Use of Constant -Weight Codes and Concatenated Codes fro a Fading Channel 14-6-5 System Design Based on the Cutoff Rate 14-6-6 Trellis -Coded Modulation 14-7 Biliographica Notes and References Problems 15 Multiuser Cjommunications 15-1 Introduction to Multiple Access Techniques 15-2 Capacity of Multiple Access Methods 15-3 Code-Division Multiple Access 15-3-1 CDMA Signal and Channel Models 15-3-2 The Optimum Receiver 15-3-3 Suboptimumu Detectors 15-3-4 Performance Characteristics of Detectors 15-4 Random Access Methods 15-4-1 ALOHA System and Protoclos 15-4-2 Carrier Sense Systems adn Protocols 15-5 Bibliographical Notes and References Problems
Appendix A The Levinson -Durbin Algorithm Appendis ErrorProbability for Multichannel Binary Signals
Appendix C Error Probabilities for Adaptive Reception of M-phase Signals C-1 Mathematical Model for an M-phase Signaling Communications Systerm C-2 Characteristic Function and Probabilty Density Function of the Phase C-3 Error Probabilties for Slowly Rayleigh Fading Channels C-4 Error Probabilities for Time-Invariant and Ricean Fading Channels Appendix D Square-Root Factorization References and Bibliography Index
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