You are previewing Digital Communications 1.
O'Reilly logo
Digital Communications 1

Book Description

The communication chain is constituted by a source and a recipient, separated by a transmission channel which may represent a portion of cable, an optical fiber, a radio channel, or a satellite link. Whatever the channel, the processing blocks implemented in the communication chain have the same foundation. This book aims to itemize.

In this first volume, after having presented the base of the information theory, we will study the source coding techniques with and without loss. Then we analyze the correcting codes for block errors, convutional and concatenated used in current systems.

Table of Contents

  1. Cover
  2. Title
  3. Copyright
  4. Preface
  5. List of Acronyms
  6. Notations
  7. Introduction
  8. 1: Introduction to Information Theory
    1. 1.1. Introduction
    2. 1.2. Review of probabilities
    3. 1.3. Entropy and mutual information
    4. 1.4. Lossless source coding theorems
    5. 1.5. Theorem for lossy source coding
    6. 1.6. Transmission channel models
    7. 1.7. Capacity of a transmission channel
    8. 1.8. Exercises
  9. 2: Source Coding
    1. 2.1. Introduction
    2. 2.2. Algorithms for lossless source coding
    3. 2.3. Sampling and quantization
    4. 2.4. Coding techniques for analog sources with memory
    5. 2.5. Application to the image and sound compression
    6. 2.6. Exercises
  10. 3: Linear Block Codes
    1. 3.1. Introduction
    2. 3.2. Finite fields
    3. 3.3. Linear block codes
    4. 3.4. Decoding of binary linear block codes
    5. 3.5. Performances of linear block codes
    6. 3.6. Cyclic codes
    7. 3.7. Applications
    8. 3.8. Exercises
  11. 4: Convolutional Codes
    1. 4.1. Introduction
    2. 4.2. Mathematical representations and hardware structures
    3. 4.3. Graphical representation of the convolutional codes
    4. 4.4. Free distance and transfer function of convolutional codes
    5. 4.5. Viterbi’s algorithm for the decoding of convolutional codes
    6. 4.6. Punctured convolutional codes
    7. 4.7. Applications
    8. 4.8. Exercises
  12. 5: Concatenated Codes and Iterative Decoding
    1. 5.1. Introduction
    2. 5.2. Soft input soft output decoding
    3. 5.3. LDPC codes
    4. 5.4. Parallel concatenated convolutional codes or turbo codes
    5. 5.5. Other classes of concatenated codes
    6. 5.6. Exercises
  13. Appendix A: Proof of the Channel Capacity of the Additive White Gaussian Noise Channel
  14. Appendix B: Calculation of the Weight Enumerator Function IRWEF of a Systematic Recursive Convolutional Encoder
  15. Bibliography
  16. Index
  17. End User License Agreement