Low-Complexity LP Decoding of Nonbinary Linear Codes
Mayur Punekar, Pascal O. Vontobel, and Mark F. Flanagan

TL;DR
This paper extends low-complexity LP decoding algorithms to nonbinary linear codes, achieving linear complexity per iteration and demonstrating comparable or improved error correction performance over certain nonbinary LDPC codes.
Contribution
The paper introduces nonbinary LCLP decoding algorithms with linear per-iteration complexity and a modified BCJR check-node calculation, expanding LP decoding to nonbinary codes.
Findings
Complexity per iteration scales linearly with block length.
Error-correcting performance is comparable or better than min-sum decoding.
Effective for nonbinary LDPC codes over Z_4, GF(4), GF(8).
Abstract
Linear Programming (LP) decoding of Low-Density Parity-Check (LDPC) codes has attracted much attention in the research community in the past few years. LP decoding has been derived for binary and nonbinary linear codes. However, the most important problem with LP decoding for both binary and nonbinary linear codes is that the complexity of standard LP solvers such as the simplex algorithm remains prohibitively large for codes of moderate to large block length. To address this problem, two low-complexity LP (LCLP) decoding algorithms for binary linear codes have been proposed by Vontobel and Koetter, henceforth called the basic LCLP decoding algorithm and the subgradient LCLP decoding algorithm. In this paper, we generalize these LCLP decoding algorithms to nonbinary linear codes. The computational complexity per iteration of the proposed nonbinary LCLP decoding algorithms scales…
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