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Title: Decoding Reed–Muller Codes Using Minimum-Weight Parity Checks
Reed–Muller (RM) codes exhibit good performance under maximum-likelihood (ML) decoding due to their highly- symmetric structure. In this paper, we explore the question of whether the code symmetry of RM codes can also be exploited to achieve near-ML performance in practice. The main idea is to apply iterative decoding to a highly-redundant parity-check (PC) matrix that contains only the minimum-weight dual codewords as rows. As examples, we consider the peeling decoder for the binary erasure channel, linear-programming and belief propagation (BP) decoding for the binary-input additive white Gaussian noise channel, and bit-flipping and BP decoding for the binary symmetric channel. For short block lengths, it is shown that near-ML performance can indeed be achieved in many cases. We also propose a method to tailor the PC matrix to the received observation by selecting only a small fraction of useful minimum-weight PCs before decoding begins. This allows one to both improve performance and significantly reduce complexity compared to using the full set of minimum-weight PCs.  more » « less
Award ID(s):
1718494
NSF-PAR ID:
10064524
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
IEEE International Symposium on Information Theory
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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