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Preface
List of Acronyms
1 Introduction
1.1 Structure of a Digital Communication System
1.2 Plan of the Book
1.3 Further Reading
Part I MODULATION AND DETECTION
2 Wireless Channels
2.1 Introduction
2.2 Mathematical Description of SISO Wireless Channels
2.2.1 Input–Output Characterization of a SISO Wireless Channel
2.2.2 Statistical Characterization of a SISO Wireless Channel
2.2.3 Reduced-Complexity Statistical Models for SISO Channels
2.3 Mathematical Description and Modeling of MIMO Wireless Channels
2.3.1 Input–Output Characterization of a MIMO Wireless Channel
2.3.2 Statistical Characterization of a MIMO Wireless Channel
2.3.3 Reduced-Complexity Statistical Modeling of MIMO Channels
2.4 Historical Notes
2.4.1 Large-Scale Fading Models
2.4.2 Small-Scale Fading Models
2.5 Further Reading
3 Digital Modulation Techniques
3.1 Introduction
3.2 General Structure of a Digital Modulator
3.3 Representation of Digital Modulated Waveforms on an Orthonormal Basis
3.4 Bandwidth of Digital Modulations
3.5 Passband PAM
3.5.1 Signal Model
3.5.2 Constellation Selection
3.5.3 Data Block Transmission with Passband PAM Signals for Frequency-Domain Equalization
3.5.4 Power Spectral Density of Linear Modulations
3.6 Continuous Phase Modulation
3.6.1 Signal Model
3.6.2 Full-Response CPM
3.6.3 Partial-Response CPM
3.6.4 Multi-h CPM
3.6.5 Alternative Representations of CPM Signals
3.6.6 Data Block Transmission with CPM Signals for Frequency-Domain Equalization
3.6.7 Power Spectral Density of Continuous Phase Modulations
3.7 OFDM
3.7.1 Introduction
3.7.2 OFDM Signal Model
3.7.3 Power Spectral Density of OFDM
3.7.4 The PAPR Problem in OFDM
3.8 Lattice-Based Multidimensional Modulations
3.8.1 Lattices: Basic Definitions and Properties
3.8.2 Elementary Constructions of Lattices
3.9 Spectral Properties of a Digital Modulation at the Output of a Wireless Channel
3.10 Historical Notes
3.10.1 Passband PAM Signaling
3.10.2 CPM Signaling
3.10.3 MCM Signaling
3.10.4 Power Spectral Density of Digital Modulations
3.11 Further Reading
4 Detection of Digital Signals over Wireless Channels: Decision Rules
4.1 Introduction
4.2 Wireless Digital Communication Systems: Modeling, Receiver Architecture and Discretization of the Received Signal
4.2.1 General Model of a Wireless Communication System
4.2.2 Receiver Architectures
4.3 Optimum Detection in a Vector Communication System
4.3.1 Description of a Vector Communication System
4.3.2 Detection Strategies and Error Probabilities
4.3.3 MAP and ML Detection Strategies
4.3.4 Diversity Reception and Some Useful Theorems about Data Detection
4.4 Mathematical Models for the Receiver Vector
4.4.1 Extraction of a Set of Sufficient Statistics from the Received Signal
4.4.2 Received Vector for PAM Signaling
4.4.3 Received Vector for CPM Signaling
4.4.4 Received Vector for OFDM Signaling
4.5 Decision Strategies in the Presence of Channel Parameters: Optimal Metrics and Performance Bounds
4.5.1 Signal Model and Algorithm Classification
4.5.2 Detection for Transmission over of a Known Channel
4.5.3 Detection in the Presence of a Statistically Known Channel
4.5.4 Detection in the Presence of an Unknown Channel
4.6 Expectation–Maximization Techniques for Data Detection
4.6.1 The EM Algorithm
4.6.2 The Bayesian EM Algorithm
4.6.3 Initialization and Convergence of EM-Type Algorithms
4.6.4 Other EM Techniques
4.7 Historical Notes
4.8 Further Reading
5 Data-Aided Algorithms for Channel Estimation
5.1 Channel Estimation Techniques
5.1.1 Introduction
5.1.2 Feedforward Estimation
5.1.3 Recursive Estimation
5.1.4 The Principle of Per-Survivor Processing
5.2 Cram´er–Rao Bounds for Data-Aided Channel Estimation
5.3 Data-Aided CIR Estimation Algorithms in PATs
5.3.1 PAT Modeling and Optimization
5.3.2 A Signal Processing Perspective on PAT Techniques
5.4 Extensions to MIMO Channels
5.4.1 Channel Estimation in SC MIMO PATs
5.4.2 Channel Estimation in MC MIMO PATs
5.5 Historical Notes
5.6 Further Reading
6 Detection of Digital Signals over Wireless Channels: Channel Equalization Algorithms
6.1 Introduction
6.2 Channel Equalization of Single-Carrier Modulations: Known CIR
6.2.1 Channel Equalization in the Time Domain
6.2.2 Channel Equalization in the Frequency Domain
6.3 Channel Equalization of Multicarrier Modulations: Known CIR
6.3.1 Optimal Detection in the Absence of IBI and ICI
6.3.2 ICI Cancelation Techniques for Time-Varying Channels
6.3.3 Equalization Strategies for IBI Compensation
6.4 Channel Equalization of Single Carrier Modulations: Statistically Known CIR
6.4.1 MLSD
6.4.2 Other Equalization Strategies with Frequency-Flat Fading
6.5 Channel Equalization of Multicarrier Modulations: Statistically Known CIR
6.6 Joint Channel and Data Estimation: Single-Carrier Modulations
6.6.1 Adaptive MLSD
6.6.2 PSP MLSD
6.6.3 Adaptive MAPBD/MAPSD
6.6.4 Equalization Strategies Employing Reference-Based Channel Estimators with Frequency-Flat Fading
6.7 Joint Channel and Data Estimation: Multicarrier Modulations
6.7.1 Pilot-Based Equalization Techniques
6.7.2 Semiblind Equalization Techniques
6.8 Extensions to the MIMO Systems
6.8.1 Equalization Techniques for Single-Carrier MIMO Communications
6.8.2 Equalization Techniques for MIMO-OFDM Communications
6.9 Historical Notes
6.10 Further Reading
Part II INFORMATION THEORY AND CODING SCHEMES
7 Elements of Information Theory
7.1 Introduction
7.2 Capacity for Discrete Sources and Channels
7.2.1 The Discrete Memoryless Channel
7.2.2 The Continuous-Output Channel
7.2.3 Channel Capacity
7.3 Capacity of MIMO Fading Channels
7.3.1 Frequency-Flat Fading Channel
7.3.2 MIMO Channel Capacity
7.3.3 Random Channel
7.4 Historical Notes
7.5 Further Reading
8 An Introduction to Channel Coding Techniques
8.1 Basic Principles
8.2 Interleaving
8.3 Taxonomy of Channel Codes
8.4 Taxonomy of Coded Modulations
8.5 Organization of the Following Chapters
8.6 Historical Notes
8.7 Further Reading
9 Classical Coding Schemes
9.1 Block Codes
9.1.1 Introduction
9.1.2 Structure of Linear Codes over GF(q)
9.1.3 Properties of Linear Block Codes
9.1.4 Cyclic Codes
9.1.5 Other Relevant Linear Block Codes
9.1.6 Decoding Techniques for Block Codes
9.1.7 Error Performance
9.2 Convolutional Codes
9.2.1 Introduction
9.2.2 Properties of Convolutional Codes
9.2.3 Maximum Likelihood Decoding of Convolutional Codes
9.2.4 MAP Decoding of Convolutional Codes
9.2.5 Sequential Decoding of Convolutional Codes
9.2.6 Error Performance of ML Decoding of Convolutional Codes
9.3 Classical Concatenated Coding
9.3.1 Parallel Concatenation: Product Codes
9.3.2 Serial Concatenation: Outer RS Code
9.4 Historical Notes
9.4.1 Algebraic Coding
9.4.2 Probabilistic Coding
9.5 Further Reading
10 Modern Coding Schemes
10.1 Introduction
10.2 Concatenated Convolutional Codes
10.2.1 Parallel Concatenated Coding Schemes
10.2.2 Serially Concatenated Coding Schemes
10.2.3 Hybrid Concatenated Coding Schemes
10.3 Concatenated Block Codes
10.4 Other Modern Concatenated Coding Schemes
10.4.1 Repeat and Accumulate Codes
10.4.2 Serial Concatenation of Coding Schemes and Differential Modulations
10.5 Iterative Decoding Techniques for Concatenated Codes
10.5.1 The Turbo Principle
10.5.2 SiSo Decoding Algorithms
10.5.3 Applications
10.5.4 Performance Bounds
10.6 Low-Density Parity Check Codes
10.6.1 Definition and Classification
10.6.2 Graphic Representation of LDPC Codes via Tanner Graphs
10.6.3 Minimum Distance and Weight Spectrum
10.6.4 LDPC Code Design Approaches
10.6.5 Efficient Algorithms for LDPC Encoding
10.7 Decoding Techniques for LDPC Codes
10.7.1 Introduction to Decoding via Message Passing Algorithms
10.7.2 SPA and MSA
10.7.3 Technical Issues on LDPC Decoding via MP
10.8 Codes on Graphs
10.9 Historical Notes
10.10 Further Reading
11 Signal Space Codes
11.1 Introduction
11.2 Trellis Coding with Expanded Signal Sets
11.2.1 Code Construction
11.2.2 Decoding Algorithms
11.2.3 Error Performance
11.3 Bit-Interleaved Coded Modulation
11.3.1 Code Construction
11.3.2 Decoding Algorithms
11.3.3 Error Performance
11.4 Modulation Codes Based on Multilevel Coding
11.4.1 Code Construction for AWGN Channels
11.4.2 Multistage Decoder
11.4.3 Error Performance
11.4.4 Multilevel Codes for Rayleigh Flat Fading Channels
11.5 Space-Time Coding
11.5.1 ST Coding for Frequency-Flat Fading Channels
11.5.2 ST Coding for Frequency-Selective Fading Channels
11.6 Historical Notes
11.7 Further Reading
12 Combined Equalization and Decoding
12.1 Introduction
12.2 Noniterative Techniques
12.3 Algorithms for Combined Equalization and Decoding
12.3.1 Introduction
12.3.2 Turbo Equalization from a FG Perspective
12.3.3 Reduced-Complexity Techniques for SiSo Equalization
12.3.4 Turbo Equalization in the FD
12.3.5 Turbo Equalization in the Presence of an Unknown Channel
12.4 Extension to MIMO
12.5 Historical Notes
12.5.1 Reduced-Complexity SiSo Equalization
12.5.2 Error Performance and Convergence Speed in Turbo Equalization
12.5.3 SiSo Equalization Algorithms in the Frequency Domain
12.5.4 Use of Precoding
12.5.5 Turbo Equalization and Factor Graphs
12.5.6 Turbo Equalization for MIMO Systems
12.5.7 Related Techniques
12.6 Further Reading
Appendix A Fourier Transforms
Appendix B Power Spectral Density of Random Processes
B.1 Power Spectral Density of a Wide-Sense Stationary Random Process
B.2 Power Spectral Density of a Wide-Sense Cyclostationary Random Process
B.3 Power Spectral Density of a Bandpass Random Process
Appendix C Matrix Theory
Appendix D Signal Spaces
D.1 Representation of Deterministic Signals
D.1.1 Basic Definitions
D.1.2 Representation of Deterministic Signals via Orthonormal Bases
D.2 Representation of Random Signals via Orthonormal Bases
Appendix E Groups, Finite Fields and Vector Spaces
E.1 Groups
E.2 Fields
E.2.1 Axiomatic Definition of a Field and Finite Fields
E.2.2 Polynomials and Extension Fields
E.2.3 Other Definitions and Properties
E.2.4 Computation Techniques for Finite Fields
E.3 Vector Spaces
Appendix F Error Function and Related Functions
References
Index
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