Study of Weighted Residual Layered Belief Propagation for Decoding of LDPC Codes

TL;DR

This paper introduces the weighted residual layered belief propagation (WR-LBP) algorithm for LDPC decoding, which reduces the number of iterations needed for convergence by utilizing residuals within a layered structure.

Contribution

The paper proposes a novel WR-LBP decoding algorithm that leverages residuals in a layered framework to improve decoding efficiency for LDPC codes.

Findings

WR-LBP reduces the number of decoding iterations.

WR-LBP achieves comparable or better bit error rates.

The algorithm outperforms traditional methods in convergence speed.

Abstract

In this work, we investigate the decoding of Low-Density Parity-Check (LDPC) codes using informed dynamic scheduling algorithms that require a reduced number of iterations. In particular, we devise the weighted residual layered belief propagation (WR-LBP) decoding algorithm, which exploits the residual within a structured layer framework to speed the number of required decoding iterations. The proposed WR-LBP algorithm is assessed against important LDPC decoding algorithms, in terms of the number of iterations required for convergence and the bit error rates.