A Comparative Study of Ensemble Decoding Methods for Short Length LDPC Codes

TL;DR

This paper compares various ensemble decoding methods for short LDPC codes, highlighting their performance improvements over traditional belief propagation and emphasizing the benefits of code-structure-exploiting algorithms.

Contribution

It provides a comprehensive qualitative and quantitative comparison of multiple ensemble decoding techniques for short LDPC codes, identifying the most effective approaches.

Findings

Ensemble methods outperform traditional BP decoding.

Code-structure-exploiting algorithms like MBBP and AED show greater gains.

All evaluated methods improve decoding performance over standard BP.

Abstract

To alleviate the suboptimal performance of belief propagation (BP) decoding of short low-density parity-check (LDPC) codes, a plethora of improved decoding algorithms has been proposed over the last two decades. Many of these methods can be described using the same general framework, which we call ensemble decoding: A set of independent constituent decoders works in parallel on the received sequence, each proposing a codeword candidate. From this list, the maximum likelihood (ML) decision is designated as the decoder output. In this paper, we qualitatively and quantitatively compare different realizations of the ensemble decoder, namely multiple-bases belief propagation (MBBP), automorphism ensemble decoding (AED), scheduling ensemble decoding (SED), noise-aided ensemble decoding (NED) and saturated belief propagation (SBP). While all algorithms can provide gains over traditional BP decoding, ensemble methods that exploit the code structure, such as MBBP and AED, typically show greater performance improvements.