We propose a complexity-reducing algorithm for serial scheduled min-sum decoding that reduces the number of check nodes to process during an iteration. The check nodes to skip are chosen based on the reliability, a syndrome and a log-likelihood-ratio (LLR) value, of the incoming messages. The proposed algorithm is evaluated by computer simulations and shown to reduce the decoding complexity about 20% compared with a conventional serial scheduled min-sum decoding with small fractional decibel degradation in error correction performance.

This paper presents an improved min-sum iterative decoding scheme for regular and irregular LDPC codes. The proposed decoding scheme scales the extrinsic soft information from variable nodes to check. Different scaling factors are applied for iterations and the scaling factors are obtained by a simplified vector optimization method.