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• W3213627099 abstract "Reed–Muller (RM) codes are known for their good maximum likelihood (ML) performance in the short block-length regime. Despite being one of the oldest classes of channel codes, finding a low complexity soft-input decoding scheme is still an open problem. In this work, we present a belief propagation (BP) decoding architecture for RM codes based on their rich automorphism group. The decoding algorithm can be seen as a generalization of multiple-bases belief propagation (MBBP) using polar BP as constituent decoders. We provide extensive errorrate performance simulations and compare our results to existing decoding schemes. We report a near-ML performance for the RM(3,7)-code (e.g., 0.05 dB away from the ML bound at BLER of 10− <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>4</sup> ) at a competitive computational cost. To the best of our knowledge, our proposed decoder achieves the best performance of all iterative RM decoders presented thus far." @default.
• W3213627099 created "2021-11-22" @default.
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• W3213627099 date "2021-08-30" @default.
• W3213627099 modified "2023-09-23" @default.
• W3213627099 title "Iterative Reed–Muller Decoding" @default.
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• W3213627099 doi "https://doi.org/10.1109/istc49272.2021.9594182" @default.
• W3213627099 hasPublicationYear "2021" @default.
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