2020 IEEE International Symposium
on Information Theory
21-26 June 2020 • Los Angeles, California, USA
| Paper ID | C.1.2 | ||
| Paper Title | Efficient Maximum-Likelihood Decoding of Reed-Muller RM(m-3,m) Codes | ||
| Authors | Andrew Thangaraj, Indian Institute of Technology Madras, India; Henry D. Pfister, Duke University, United States | ||
| Session | C.1: Coding for Communications I | ||
| Presentation | Lecture | ||
| Track | Coding for Communications | ||
| Manuscript | Click here to download the manuscript | ||
| Virtual Presentation | Click here to watch in the Virtual Symposium | ||
| Abstract | Reed-Muller (RM) codes, a classical family of codes known for their elegant algebraic structure, have recently been shown to achieve capacity under maximum-likelihood (ML) decoding on the binary erasure channel and this has rekindled interest in their efficient decoding. We consider the code family RM(m-3,m) and develop a new ML decoder, for transmission over the binary symmetric channel, that exploits their large symmetry group. The new decoder has lower complexity than an earlier method introduced by Seroussi and Lempel in 1983. | ||
Plan Ahead
2021 IEEE International Symposium on Information Theory
11-16 July 2021 | Melbourne, Victoria, Australia
