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List decoding

About: List decoding is a research topic. Over the lifetime, 7251 publications have been published within this topic receiving 151182 citations.


Papers
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Journal ArticleDOI
TL;DR: The proposed algorithm has almost the same complexity as the standard iterative decoding, however, it has better performance andSimulations show that the error rate can be decreased by several orders of magnitude using the proposed algorithm.
Abstract: This paper investigates decoding of low-density parity-check (LDPC) codes over the binary erasure channel (BEC). We study the iterative and maximum-likelihood (ML) decoding of LDPC codes on this channel. We derive bounds on the ML decoding of LDPC codes on the BEC. We then present an improved decoding algorithm. The proposed algorithm has almost the same complexity as the standard iterative decoding. However, it has better performance. Simulations show that we can decrease the error rate by several orders of magnitude using the proposed algorithm. We also provide some graph-theoretic properties of different decoding algorithms of LDPC codes over the BEC which we think are useful to better understand the LDPC decoding methods, in particular, for finite-length codes.

184 citations

Journal ArticleDOI
TL;DR: This letter presents the first successful method for iterative stochastic decoding of state-of-the-art low-density parity-check (LDPC) codes and has a significant potential for high-throughput and/or low complexity iterative decoding.
Abstract: This letter presents the first successful method for iterative stochastic decoding of state-of-the-art low-density parity-check (LDPC) codes. The proposed method shows the viability of the stochastic approach for decoding LDPC codes on factor graphs. In addition, simulation results for a 200 and a 1024 length LDPC code demonstrate the near-optimal performance of this method with respect to sum-product decoding. The proposed method has a significant potential for high-throughput and/or low complexity iterative decoding.

184 citations

Journal ArticleDOI
TL;DR: A stopping criterion which reduces the average number of iterations at the expense of very little performance degradation is proposed for this combined decoding approach to bridge the error performance gap between belief propagation decoding which remains suboptimum, and maximum likelihood decoding which is too complex to be implemented for the codes considered.
Abstract: In this paper, reliability based decoding is combined with belief propagation (BP) decoding for low-density parity check (LDPC) codes. At each iteration, the soft output values delivered by the BP algorithm are used as reliability values to perform reduced complexity soft decision decoding of the code considered. This approach allows to bridge the error performance gap between belief propagation decoding which remains suboptimum, and maximum likelihood decoding which is too complex to be implemented for the codes considered. Trade-offs between decoding complexity and error performance are also investigated. In particular, a stopping criterion which reduces the average number of iterations at the expense of very little performance degradation is proposed for this combined decoding approach. Simulation results for several Gallager (1963, 1968) LDPC codes and different set cyclic codes of hundreds of information bits are given and elaborated.

183 citations

Journal ArticleDOI
TL;DR: The MAP decoding algorithm of Bahl et al. (1974) is extended to the case of tail-biting trellis codes and an algorithm is given that is based on finding an eigenvector, and another that avoids this.
Abstract: We extend the MAP decoding algorithm of Bahl et al. (1974) to the case of tail-biting trellis codes. An algorithm is given that is based on finding an eigenvector, and another that avoids this. Several examples are given. The algorithm has application to turbo decoding and source-controlled channel decoding.

183 citations

Book ChapterDOI
Shuhong Gao1
01 Jan 2003
TL;DR: A new algorithm is developed for decoding Reed-Solomon codes that uses fast Fourier transforms and computes the message symbols directly without explicitly finding error locations or error magnitudes.
Abstract: A new algorithm is developed for decoding Reed-Solomon codes. It uses fast Fourier transforms and computes the message symbols directly without explicitly finding error locations or error magnitudes. In the decoding radius (up to half of the minimum distance), the new method is easily adapted for error and erasure decoding. It can also detect all errors outside the decoding radius. Compared with the BerlekampMassey algorithm, discovered in the late 1960’s, the new method seems simpler and more natural yet it has a similar time complexity.

181 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202384
2022153
202179
202078
201982
201894