English

Improved linear programming decoding of LDPC codes and bounds on the minimum and fractional distance

Information Theory 2016-11-17 v1 math.IT

Abstract

We examine LDPC codes decoded using linear programming (LP). Four contributions to the LP framework are presented. First, a new method of tightening the LP relaxation, and thus improving the LP decoder, is proposed. Second, we present an algorithm which calculates a lower bound on the minimum distance of a specific code. This algorithm exhibits complexity which scales quadratically with the block length. Third, we propose a method to obtain a tight lower bound on the fractional distance, also with quadratic complexity, and thus less than previously-existing methods. Finally, we show how the fundamental LP polytope for generalized LDPC codes and nonbinary LDPC codes can be obtained.

Keywords

Cite

@article{arxiv.1012.1425,
  title  = {Improved linear programming decoding of LDPC codes and bounds on the minimum and fractional distance},
  author = {David Burshtein and Idan Goldenberg},
  journal= {arXiv preprint arXiv:1012.1425},
  year   = {2016}
}

Comments

17 pages, 8 figures, Submitted to IEEE Transactions on Information Theory

R2 v1 2026-06-21T16:54:39.080Z