Complexity-reducing Algorithm for Serial Min-sum Decoding

Michaelraj Kingston Roberts, Elizabeth Sunny

Hironori Uchikawa, Kohsuke Harada

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.

Hironori Uchikawa, Kohsuke Harada, 康彦 田邉

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.

Kazuhiko Yamaguchi

Ivan B. Djordjević, Lei Xu, Ting Wang

Two reduced-complexity (RC) LDPC decoders, which can be used in combination with large-girth LDPC codes to enable beyond 400 Gb/s serial optical transmission, are proposed. We show that optimally attenuated RC min-sum sum algorithm performs only 0.45 dB worse than conventional sum-product algorithm, while having lower storage memory requirements and much lower latency.

V. Sh. Le