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LDPC Codes Achieve List Decoding Capacity

Information Theory 2024-07-11 v4 Computational Complexity Combinatorics math.IT

Abstract

We show that Gallager's ensemble of Low-Density Parity Check (LDPC) codes achieves list-decoding capacity with high probability. These are the first graph-based codes shown to have this property. This result opens up a potential avenue towards truly linear-time list-decodable codes that achieve list-decoding capacity. Our result on list decoding follows from a much more general result: any local\textit{local} property satisfied with high probability by a random linear code is also satisfied with high probability by a random LDPC code from Gallager's distribution. Local properties are properties characterized by the exclusion of small sets of codewords, and include list-decodability, list-recoverability and average-radius list-decodability. In order to prove our results on LDPC codes, we establish sharp thresholds for when local properties are satisfied by a random linear code. More precisely, we show that for any local property P\mathcal{P}, there is some RR^* so that random linear codes of rate slightly less than RR^* satisfy P\mathcal{P} with high probability, while random linear codes of rate slightly more than RR^*, with high probability, do not. We also give a characterization of the threshold rate RR^*.

Keywords

Cite

@article{arxiv.1909.06430,
  title  = {LDPC Codes Achieve List Decoding Capacity},
  author = {Jonathan Mosheiff and Nicolas Resch and Noga Ron-Zewi and Shashwat Silas and Mary Wootters},
  journal= {arXiv preprint arXiv:1909.06430},
  year   = {2024}
}

Comments

39 pages, 3 figures