
This paper proposes a new iterative soft-decision decoding algorithm which combines list decoding and adaptive belief propagation (ABP) algorithm for short Reed-Solomon (RS) codes. The proposed algorithm generates a list of codewords by restarting the decoder with log-likelihood ratio saturations to the dynamically selected suspicious bits based on an up-to-date best decoded codeword. The suspicious bits are selected according to a joint evaluation of the decoded codeword and the initial channel information. The damping coefficient used in the ABP decoder is set to be proportional to the channel noise variance to achieve a proper convergence speed for the decoder at different SNRs. The performance of the proposed algorithm for short RS codes is investigated. It shows that the proposed algorithm brings a considerable coding gain for short RS codes over additive white Gaussian noise channels.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 5 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
