Improvements in belief-propagation decoding based on averaging information from decoder and correction of clusters of nodes

In this letter we provide several methods to improve belief-propagation (BP) decoding of low-density parity-check codes. The methods use additional processing of the decoded information during the decoding process and are grouped into two categories. The first category is useful in the waterfall performance region and is based on processing averaged information obtained from the decoder. Several choices of the feedback information utilized in additional processing are introduced. The second category is useful in the error-floor performance region and is based on fixing clusters of symbols simultaneously, again utilizing the information obtained by monitoring the decoder. We demonstrate on a code example that our methods achieve sizeable gains compared to the original BP decoder