| Preface | p. xi |
| Introduction of Coded Digital Communication Systems | p. 1 |
| Introduction | p. 1 |
| Elements of a Digital Communication System | p. 2 |
| Data Source and Data Sink | p. 2 |
| Channel Encoder and Channel Decoder | p. 2 |
| Modulator, Transmission Path, and Demodulator | p. 3 |
| Channel Models | p. 7 |
| References | p. 10 |
| Structures of Convolutional Codes | p. 11 |
| Encoding and Mathematical Model of Convolutional Codes | p. 11 |
| Polynomial Matrix Representation of Convolutional Codes | p. 19 |
| Error Propagation Effect and Code Design | p. 24 |
| Algebraic Structures of Generator Polynomial Matrix G(D) | p. 30 |
| Algebraic Structures of Syndrome-Former Polynomial Matrix H[superscript T](D) | p. 33 |
| Systematic Convolutional Encoder With Feedback | p. 36 |
| Graphical Representations of Convolutional Codes | p. 40 |
| Encoder Tree and Trellis Diagrams | p. 40 |
| Encoder State Diagram | p. 43 |
| Syndrome-Former Trellis Diagram | p. 44 |
| Distance Properties of Convolutional Codes | p. 47 |
| Generating Function of Convolutional Codes | p. 51 |
| References | p. 55 |
| Suboptimal and Optimal Decoding of Convolutional Codes | p. 57 |
| Introduction | p. 57 |
| Sliding Block Decoding | p. 59 |
| Maximum-Likelihood Viterbi Algorithm Decoding | p. 63 |
| Hard-Decision Viterbi Algorithm Decoding | p. 64 |
| Soft-Decision Viterbi Algorithm Decoding | p. 70 |
| Syndrome-Former Trellis Decoding | p. 73 |
| Scarce-State-Transition-Type Viterbi Algorithm Decoding | p. 74 |
| Scarce-State-Transition-Type Syndrome-Former Trellis Decoding | p. 79 |
| Performance of Hard-Decision Maximum-Likelihood Decoding | p. 80 |
| Performance of Soft-Decision Maximum-Likelihood Decoding | p. 83 |
| Computer Simulation Results and Discussion | p. 84 |
| References | p. 87 |
| Sequential Decoding of Convolutional Codes | p. 89 |
| Introduction | p. 89 |
| Fano Metric | p. 89 |
| Stack Algorithm Decoding | p. 91 |
| Fano Algorithm Decoding | p. 92 |
| References | p. 100 |
| Encoding and Decoding of Punctured Convolutional Codes | p. 101 |
| Introduction | p. 101 |
| Encoding of Punctured Convolutional Codes | p. 101 |
| Maximum-Likelihood Decoding of Punctured Convolutional Codes | p. 105 |
| Performance of Punctured Convolutional Codes | p. 109 |
| Concept of Rate-Compatible Punctured Convolutional Codes | p. 110 |
| Maximum-Likelihood Decoding of Rate-Compatible Punctured Convolutional Codes | p. 111 |
| Computer Simulation Results and Discussion | p. 112 |
| References | p. 115 |
| Majority-Logic Decoding of Convolutional Codes | p. 117 |
| Introduction | p. 117 |
| Hard-Decision Majority-Logic Decoding | p. 118 |
| Majority-Logic Definite Decoding | p. 123 |
| Majority-Logic Feedback Decoding | p. 131 |
| Error Propagation Effect | p. 139 |
| Performance of Hard-Decision Majority-Logic Decoding | p. 141 |
| Soft-Decision Majority-Logic Decoding | p. 141 |
| Computer Simulation Results | p. 143 |
| References | p. 146 |
| Combined Convolutional Coding and Modulation | p. 149 |
| Introduction | p. 149 |
| Two-Dimensional Trellis-Coded Modulation | p. 154 |
| Phase-Invariant Convolutional Codes | p. 160 |
| 90 Degree Phase-Invariant Convolutional Codes | p. 163 |
| Multidimensional Lattice Trellis-Coded Modulation | p. 167 |
| Partitioning of Multidimensional Lattices | p. 168 |
| Signal Mapping Rules and Phase-Invariant Code Construction | p. 175 |
| Multidimensional Viterbi Algorithm Decoding | p. 181 |
| Advantages of Using 2N-Dimensional Lattice TCM Scheme | p. 184 |
| Multidimensional M-PSK Trellis-Coded Modulation | p. 185 |
| Partitioning of Multidimensional M-PSK Constellations | p. 186 |
| Four-Dimensional M-PSK TCM: Signal Mapping Rules and Phase-Invariant Code Construction | p. 191 |
| Eight-Dimensional M-PSK TCM: Signal Mapping Rules and Phase-Invariant Code Construction | p. 194 |
| Multidimensional Viterbi Algorithm Decoding | p. 198 |
| Advantages of Using Multidimensional M-PSK TCM Scheme | p. 204 |
| References | p. 205 |
| Combined Coding, Modulation, and Equalization | p. 209 |
| Introduction | p. 209 |
| Nonlinear (Decision-Feedback) Equalizer | p. 210 |
| Coded System Model and Assumptions | p. 213 |
| Combined Trellis Diagram | p. 215 |
| Full-State Combined Trellis | p. 216 |
| Reduced-State Combined Trellis | p. 217 |
| Combined Equalization and Trellis Decoding | p. 218 |
| Computer Simulation Results | p. 219 |
| References | p. 222 |
| Applications of Convolutional Codes | p. 225 |
| Introduction | p. 225 |
| Applications to Space Communications | p. 225 |
| Pioneer Missions | p. 225 |
| Voyager Mission | p. 226 |
| Galileo Mission | p. 228 |
| Applications to Satellite Communications | p. 229 |
| Applications to Mobile Communications | p. 230 |
| GSM Digital Radio System | p. 230 |
| Applications to Voice-Band Data Communications | p. 236 |
| References | p. 243 |
| Connection Vectors of Convolutional Codes for Viterbi Decoding | p. 245 |
| Connection Vectors of Convolutional Codes for Sequential Decoding | p. 249 |
| Puncturing Matrix for Punctured and Rate-Compatible Punctured Convolutional Codes | p. 251 |
| Generator Polynomials for Self-Orthogonal Systematic Convolutional Codes | p. 263 |
| Generator Polynomial Matrix for Two-Dimensional Linear Trellis Codes | p. 265 |
| Encoder Trellis Program | p. 269 |
| Viterbi Codec Programs | p. 283 |
| About the Author | p. 307 |
| Index | p. 309 |
| Table of Contents provided by Syndetics. All Rights Reserved. |
