Book contents
- Frontmatter
- Contents
- Preface
- Abbreviations
- 1 Introduction
- 2 Basics
- 3 Erasure Channel Models and Bounds
- 4 Low-Density Parity-Check Codes
- 5 Weight Distribution and Minimum Distance of LDPC Codes
- 6 Iterative and Maximum-Likelihood Decoding of LDPC Codes
- 7 Iterative LDPC Decoder Analysis
- 8 Maximum-Likelihood LDPC Decoder Analysis
- 9 Low-Density Parity-Check Codes: Generalizations
- 10 Polar Codes
- 11 Fountain Codes
- Appendix A Applications of Erasure Codes
- Appendix B Random Matrices over Finite Fields
- Index
- References
11 - Fountain Codes
Published online by Cambridge University Press: 25 February 2026
Book contents
- Frontmatter
- Contents
- Preface
- Abbreviations
- 1 Introduction
- 2 Basics
- 3 Erasure Channel Models and Bounds
- 4 Low-Density Parity-Check Codes
- 5 Weight Distribution and Minimum Distance of LDPC Codes
- 6 Iterative and Maximum-Likelihood Decoding of LDPC Codes
- 7 Iterative LDPC Decoder Analysis
- 8 Maximum-Likelihood LDPC Decoder Analysis
- 9 Low-Density Parity-Check Codes: Generalizations
- 10 Polar Codes
- 11 Fountain Codes
- Appendix A Applications of Erasure Codes
- Appendix B Random Matrices over Finite Fields
- Index
- References
Summary
In Chapter 11, we address an alternative paradigm for erasure coding that exploits feedback from (multiple) receivers to the transmitter. Here, the receivers are assumed to be interested in the same content, and the transmission takes place over a broadcast channel. The feedback is employed to adapt “on the fly” the coding rate to the channel conditions. This approach, which shares several similarities with the framework of rate-compatible codes with hybrid automatic retransmission query ARQ, relies on the so-called fountain codes. Two well-established classes of fountain codes are discussed, namely the class of LT codes (strongly related to LDPC codes) and the class of Raptor codes.
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- Coding for Erasure Channels , pp. 288 - 308Publisher: Cambridge University PressPrint publication year: 2026
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