Generalized Belief Propagation to break trapping sets in LDPC codesReport as inadecuate

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1 IETR - Institut d-Electronique et de Télécommunications de Rennes 2 ETIS - Equipes Traitement de l-Information et Systèmes

Abstract : In this paper, we focus on the Generalized Belief Propagation GBP algorithm to solve trapping sets in Low-Density Parity-Check LDPC codes. Trapping sets are topological structures in Tanner graphs of LDPC codes that are not correctly decoded by Belief Propagation BP, leading to exhibit an error-floor in the bit-error rate. Stemming from statistical physics of spin glasses, GBP consists in passing messages between groups of Tanner graph nodes. Provided a well-suited grouping, this algorithm proves to be a powerful decoder as it may lower harmful topological effects of the Tanner graph. We then propose to use GBP to break trapping sets and create a new decoder to outperform BP and to defeat error-floor.

Keywords : LDPC codes Generalized Belief Propagation trapping sets error-floor local clustering

Author: Jean-Christophe Sibel - Sylvain Reynal - David Declercq -



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