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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