LOW-DENSITY PARITY-CHECK CODES ACHIEVE LIST-DECODING CAPACITY

Jonathan Mosheiff, Nicolas Resch, Noga Ron-Zewi, Shashwat Silas, Mary Wootters

Research output: Contribution to journalArticlepeer-review

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 toward 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 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, there is some R so that random linear codes of rate slightly less than R satisfy P with high probability, while random linear codes of rate slightly more than R, with high probability, do not.

Original languageEnglish
Pages (from-to)FOCS20-38-FOCS20-73
JournalSIAM Journal on Computing
Volume53
Issue number6
DOIs
StatePublished - 1 Jan 2024
Externally publishedYes

Keywords

  • Gallagher codes
  • LDPC codes
  • list-decoding
  • local properties
  • random linear codes
  • threshold

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics

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