Title :
Analysis and design of ultra-sparse non-binary cluster-LDPC codes
Author :
Declercq, David ; Savin, Valentin ; Sy, Lam Pham
Author_Institution :
ETIS, Univ. Cergy-Pontoise, Cergy-Pontoise, France
Abstract :
This paper continues a previous work on non-binary cluster-LDPC codes. Such codes are defined by locally dense parity-check matrices, with (possibly rectangular) dense clusters of bits, but which are cluster-wise sparse. We derive a lower bound on the minimum distance of non-binary cluster-LDPC codes that is based on the topological properties of the underlying bipartite graph. We also propose an optimization procedure, which allows designing finite length codes with large minimum distance, even in the extreme case of codes defined by ultra-sparse graphs, i.e. graphs with all symbol-nodes of degree dv = 2. Furthermore, we provide asymptotic thresholds of ensembles of non-binary cluster-LDPC codes, which are computed exactly under the Belief Propagation decoding, and upper-bounded under the Maximum a Posteriori (MAP) decoding. We show that the MAP-threshold upper bounds, which are conjunctured to be tight, quickly approach the channel capacity, which confirms the excellent minimal distance properties of non-binary cluster-LDPC codes.
Keywords :
channel capacity; channel coding; graph theory; maximum likelihood decoding; optimisation; parity check codes; MAP decoding; MAP-threshold upper bounds; asymptotic thresholds; belief propagation decoding; bipartite graph; channel capacity approach; finite length codes; locally dense parity-check matrices; lower bound; maximum a posteriori decoding; optimization procedure; ultrasparse graphs; ultrasparse nonbinary cluster-LDPC code design; Algorithm design and analysis; Bipartite graph; Clustering algorithms; Decoding; Iterative decoding; Optimization;
Conference_Titel :
Information Theory Proceedings (ISIT), 2012 IEEE International Symposium on
Conference_Location :
Cambridge, MA
Print_ISBN :
978-1-4673-2580-6
Electronic_ISBN :
2157-8095
DOI :
10.1109/ISIT.2012.6283973