Preface Chapter 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 1.6 Bibliographical Notes and References Chapter 2 Deterministic and Random Signal Analysis 2.1 Bandpass and Lowpass Signal Representation 2.1-1 Bandpass and Lowpass Signals 2.1-2 Lowpass Equivalent of Bandpass Signals 2.1-3 Energy Considerations 2.1-4 Lowpass Equivalent of a Bandpass System 2.2 Signal Space Representation of Waveforms 2.2-1 Vector Space Concepts 2.2-2 Signal Space Concept 2.2-3 Orthogonal Expansions of Signals 2.2-4 Gram-Schmidt Procedure 2.3 Some Useful Random Variables 2.4 Bounds on Tail Probabilities 2.5 Limit Theorems for Sums of Random Variables 2.6 Complex Random Variables 2.6-1 Complex Random Vectors 2.7 Random Processes 2.7-1 Wide-Sense Stationary Random Processes 2.7-2 Cyclostationary Random Processes 2.7-3 Proper and Circular Random Processes 2.7-4 Markov Chains 2.8 Series Expansion of Random Processes 2.8-1 Sampling Theorem for Band-Limited Random Processes 2.8-2 The Karhunen-Lo?ve Expansion 2.9 Bandpass and Lowpass Random Processes 2.10 Bibliographical Notes and References Problems Chapter 3 Digital Modulation Schemes 3.1 Representation of Digitally Modulated Signals 3.2 Memoryless Modulation Methods 3.2-1 Pulse Amplitude Modulation (PAM) 3.2-2 Phase Modulation 3.2-3 Quadrature Amplitude Modulation 3.2-4 Multidimensional Signaling 3.3 Signaling Schemes with Memory 3.3-1 Continuous-Phase Frequency-Shift Keying (CPFSK) 3.3-2 Continuous-Phase Modulation (CPM) 3.4 Power Spectrum of Digitally Modulated Signals 3.4-1 Power Spectral Density of a Digitally Modulated Signal with Memory 3.4-2 Power Spectral Density of Linearly Modulated Signals 3.4-3 Power Spectral Density of Digitally Modulated Signals with Finite Memory 3.4-4 Power Spectral Densities of CPFSK and CPM Signals 3.5 Bibliographical Notes and References Problems
Chapter 4 Optimum Receivers for AWGN Channels 4.1 Waveform and Vector Channel Models 4.1-1 Optimal Detection for a General Vector Channel 4.2 Waveform and Vector AWGN Channels 4.2-1 Optimal Detection for the Vector AWGN Channel 4.2-2 Implementation of the Optimal Receiver for AWGN Channels 4.2-3 A Union Bound on the Probability of Error of Maximum Likelihood Detection 4.3 Optimal Detection and Error Probability for Band-Limited Signaling 4.3-1 Optimal Detection and Error Probability for ASK or PAM Signaling 4.3-2 Optimal Detection and Error Probability for PSK Signaling 4.3-3 Optimal Detection and Error Probability for QAM Signaling 4.3-4 Demodulation and Detection 4.4 Optimal Detection and Error Probability for Power-Limited Signaling 4.4-1 Optimal Detection and Error Probability for Simplex Signaling 4.4-2 Optimal Detection and Error Probability for Biorthogonal Signaling 4.4-3 Optimal Detection and Error Probability for Simplex Signaling …… Chapter 5 Carrier and Symbol Synchronization Chapter 6 An Introduction to Information Theory Chapter 7 Linear Block Codes Chapter 8 Trellis and Graph Based Codes Chapter 9 Digital Communication Through Band-Limited Channels Chapter 10 Adaptive Equalization Chapter 11 Multichannel and Multicarrier Systems Chapter 12 Spread Spectrum Signals for Digital Communications Chapter 13 Fading Channels I: Characterization and Signaling Chapter 14 Fading Channels II: Capacity and Coding Chapter 15 Multiple-Antenna Systems Chapter 16 Multiuser Communications Appendix A Matrices Appendix B Error Probability for Multichannel Binary Signals Appendix C Error Probabilities for Adaptive Reception of M-Phase Signals Appendix D Square Root Factorization References and Bibliography Index