4.7 Article

On the Efficiency of Polar-Like Decoding for Symmetric Codes

期刊

IEEE TRANSACTIONS ON COMMUNICATIONS
卷 70, 期 1, 页码 163-170

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCOMM.2021.3121442

关键词

Codes; Maximum likelihood decoding; Polar codes; Codecs; Boolean functions; Complexity theory; Symmetric matrices; Reed-Muller codes; polar codes; list decoding; permutation decoding

资金

  1. EPFL

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The recently introduced polar codes are a breakthrough in coding theory due to their capacity-achieving property, but the decoding complexity is high. This paper explores the factors affecting the decoding complexity by studying the group of symmetries of the codes and permutation decoding algorithms.
The recently introduced polar codes constitute a breakthrough in coding theory due to their capacity-achieving property. This goes hand in hand with a quasilinear construction, encoding, and successive cancellation list decoding procedures based on the Plotkin construction. The decoding algorithm can be applied with slight modifications to Reed-Muller or eBCH codes, that both achieve the capacity of erasure channels, although the list size needed for good performance grows too fast to make the decoding practical even for moderate block lengths. The key ingredient for proving the capacity-achieving property of Reed-Muller and eBCH codes is their group of symmetries. It can be plugged into the concept of Plotkin decomposition to design various permutation decoding algorithms. Although such techniques allow to outperform the straightforward polar-like decoding, the complexity stays impractical. In this paper, we show that although invariance under a large automorphism group is valuable in a theoretical sense, it also ensures that the list size needed for good performance grows exponentially. We further establish the bounds that arise if we sacrifice some of the symmetries. Although the theoretical analysis of the list decoding algorithm remains an open problem, our result provides an insight into the factors that impact the decoding complexity.

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