
arXiv: 1108.0840
The relation between parity-check matrices of quasi-cyclic (QC) low-density parity-check (LDPC) codes and biadjacency matrices of bipartite graphs supports searching for powerful LDPC block codes. Using the principle of tailbiting, compact representations of bipartite graphs based on convolutional codes can be found. Bounds on the girth and the minimum distance of LDPC block codes constructed in such a way are discussed. Algorithms for searching iteratively for LDPC block codes with large girth and for determining their minimum distance are presented. Constructions based on all-ones matrices, Steiner Triple Systems, and QC block codes are introduced. Finally, new QC regular LDPC block codes with girth up to 24 are given.
Submitted to IEEE Transactions on Information Theory in February 2011
FOS: Computer and information sciences, biadjacency matrix, Tanner graph, Computer Science - Information Theory, Information Theory (cs.IT), tailbiting, Electrical Engineering, Electronic Engineering, Information Engineering, girth, LDPC code, convolutional code, minimum distance
FOS: Computer and information sciences, biadjacency matrix, Tanner graph, Computer Science - Information Theory, Information Theory (cs.IT), tailbiting, Electrical Engineering, Electronic Engineering, Information Engineering, girth, LDPC code, convolutional code, minimum distance
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 59 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
