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LDPC Codes Achieve List Decoding Capacity

Conference Paper Session 4A Algorithms and Complexity ยท Theoretical Computer Science

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 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-decoding, list-recovery and average-radius list-decoding. 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 $\mathcal{P}$, there is some $R^{\ast}$ so that random linear codes of rate slightly less than $R^{\ast}$ satisfy $\mathcal{P}$ with high probability, while random linear codes of rate slightly more than $R^{\ast}$ with high probability do not. We also give a characterization of the threshold rate $R^{\ast}$. This is an extended abstract. The full version is available at https: //arxiv. org/abs/1909. 06430

Authors

Keywords

  • Parity check codes
  • Linear codes
  • Decoding
  • Computer science
  • Capacity planning
  • Bipartite graph
  • Task analysis
  • Low-density Parity-check Codes
  • Low-density Parity-check
  • List-decoding Capacity
  • High Probability
  • Local Properties
  • Codeword
  • Random Code
  • Linear Code
  • Parity-check
  • Building Blocks
  • Efficient Algorithm
  • Line Of Work
  • Fourier Analysis
  • Random Matrix
  • Binary Code
  • Random Graph
  • Almost Surely
  • Finite Field
  • Coding Theory
  • Linear-time Algorithm
  • Smooth Distribution
  • Reed-Solomon Codes
  • Code Size
  • List Size
  • General Theorem
  • Parity-check Matrix
  • Alphabet Size
  • LDPC
  • List Decoding
  • Local Property
  • Thershold

Context

Venue
IEEE Symposium on Foundations of Computer Science
Archive span
1975-2025
Indexed papers
3809
Paper id
244764082563592258