Author(s)

Huanming Zhang

Electronics and Information Engineering Institute, Foshan University, Foshan, China.

LDPC codes are finding increasing use in applications requiring reliable and highly efficient information transfer over bandwidth. An LDPC code is defined by a sparse parity-check matrix and can be described by a bipartite graph called Tanner graph. Loops in Tanner graph prevent the sum-product algorithm from converging. Further, loops, especially short loops, degrade the performance of LDPC decoder, because they affect the independence of the extrinsic information exchanged in the iterative decoding. This paper, by graph theory, deduces cut-node tree graph of LDPC code, and depicts it with matrix. On the basis of tree matrix algorithm, whole depictions of loops can be figured out, providing of foundation for further research of relations between loops and LDPC codes’ performance.

LDPC, Belief Propagation (BP), Graph, Iterative Decoding, Loop, Cycle

Zhang, H. (2014) Tree Matrix Algorithm of LDPC Codes. Journal of Signal and Information Processing, 5, 191-197. doi: 10.4236/jsip.2014.54020.