Digital Communications 1

Didier Le Ruyet received his Eng. Degree and his Ph. D. degree from Conservatoire National des Arts et Métiers (CNAM) in 1994 and 2001 respectively.  In 2009, he received the “Habilitation à diriger des recherches” from Paris XIII University. He is full professor at CNAM since 2010 and deputy director of the center for research in Computer Science and Telecommunications (CEDRIC). He has published about 100 papers in refereed journals and conference proceedings. His main research and teaching activities lie in the areas of digital communication, wireless communication and signal processing including channel coding and multi-antenna transmission.Mylène Pischella received her engineering degree and her phD in electronics and telecommunications from Télécom ParisTech. She is an associate professor at  Conservatoire National des Arts et Métiers (CNAM), where she is responsible of courses on digital communications, wireless communications and information theory.

• Preface xiii List of Acronyms xvNotations xixIntroduction xxiiiChapter 1 Introduction to Information Theory 11.1 Introduction 11.2 Review of probabilities 21.3 Entropy and mutual information 71.4 Lossless source coding theorems 201.5 Theorem for lossy source coding 301.6 Transmission channel models 341.7 Capacity of a transmission channel 401.8 Exercises 54Chapter 2 Source Coding 572.1 Introduction 572.2 Algorithms for lossless source coding 582.3 Sampling and quantization 692.4 Coding techniques for analog sources with memory 872.5 Application to the image and sound compression 1012.6 Exercises 116Chapter 3 Linear Block Codes 1213.1 Introduction 1213.2 Finite fields 1223.3 Linear block codes 1273.4 Decoding of binary linear block codes 1523.5 Performance of linear block codes 1723.6 Cyclic codes 1823.7 Applications 2143.8 Exercises 216Chapter 4 Convolutional Codes 2294.1 Introduction 2294.2 Mathematical representations and hardware structures 2294.3 Graphical representation of the convolutional codes 2384.4 Free distance and transfer function of convolutional codes 2424.5 Viterbi's algorithm for the decoding of convolutional codes 2464.6 Punctured convolutional codes 2494.7 Applications 2494.8 Exercises 250Chapter 5 Concatenated Codes and Iterative Decoding 2535.1 Introduction 2535.2 Soft input soft output decoding 2545.3 LDPC codes 2885.4 Parallel concatenated convolutional codes or turbo codes 3065.5 Other classes of concatenated codes 3305.6 Exercises 335Appendices 339Appendix A 341Appendix B 343Bibliography 345Index 353Summary of Volume 2 355