Reduced-complexity serial min-sum decoding

We propose a complexity-reducing method for serial 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 method is evaluated by computer simulations and shown to reduce the decoding complexity up to 70% compared with conventional serial min-sum decoding with small fractional decibel degradation in error correction performance.