Efficient Maximum-Likelihood Decoding of Reed-Muller RM(m-3,m) Codes
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Thangaraj, A; Pfister, HD
Published in: IEEE International Symposium on Information Theory - Proceedings
June 1, 2020
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.
Duke Scholars
Published In
IEEE International Symposium on Information Theory - Proceedings
DOI
ISSN
2157-8095
Publication Date
June 1, 2020
Volume
2020-June
Start / End Page
263 / 268
Citation
APA
Chicago
ICMJE
MLA
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Thangaraj, A., & Pfister, H. D. (2020). Efficient Maximum-Likelihood Decoding of Reed-Muller RM(m-3,m) Codes. In IEEE International Symposium on Information Theory - Proceedings (Vol. 2020-June, pp. 263–268). https://doi.org/10.1109/ISIT44484.2020.9174065
Thangaraj, A., and H. D. Pfister. “Efficient Maximum-Likelihood Decoding of Reed-Muller RM(m-3,m) Codes.” In IEEE International Symposium on Information Theory - Proceedings, 2020-June:263–68, 2020. https://doi.org/10.1109/ISIT44484.2020.9174065.
Thangaraj A, Pfister HD. Efficient Maximum-Likelihood Decoding of Reed-Muller RM(m-3,m) Codes. In: IEEE International Symposium on Information Theory - Proceedings. 2020. p. 263–8.
Thangaraj, A., and H. D. Pfister. “Efficient Maximum-Likelihood Decoding of Reed-Muller RM(m-3,m) Codes.” IEEE International Symposium on Information Theory - Proceedings, vol. 2020-June, 2020, pp. 263–68. Scopus, doi:10.1109/ISIT44484.2020.9174065.
Thangaraj A, Pfister HD. Efficient Maximum-Likelihood Decoding of Reed-Muller RM(m-3,m) Codes. IEEE International Symposium on Information Theory - Proceedings. 2020. p. 263–268.
Published In
IEEE International Symposium on Information Theory - Proceedings
DOI
ISSN
2157-8095
Publication Date
June 1, 2020
Volume
2020-June
Start / End Page
263 / 268