Topic
List decoding
About: List decoding is a research topic. Over the lifetime, 7251 publications have been published within this topic receiving 151182 citations.
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TL;DR: A symbol-by-symbol maximum a posteriori (MAP) decoding algorithm for high-rate convolutional codes applying reciprocal dual convolutionAL codes is presented, resulting in a reduction of the computational complexity since the number of codewords to consider is decreased.
Abstract: A symbol-by-symbol maximum a posteriori (MAP) decoding algorithm for high-rate convolutional codes applying reciprocal dual convolutional codes is presented. The advantage of this approach is a reduction of the computational complexity since the number of codewords to consider is decreased. All requirements for iterative decoding schemes are fulfilled. Since tail-biting convolutional codes are equivalent to quasi-cyclic block codes, the decoding algorithm for truncated or terminated convolutional codes is modified to obtain a soft-in/soft-out decoder for high-rate quasi-cyclic block codes which also uses the dual code because of complexity reasons. Additionally, quasi-cyclic block codes are investigated as component codes for parallel concatenation. Simulation results obtained by iterative decoding are compared with union bounds for maximum likelihood decoding. The results of a search for high-rate quasi-cyclic block codes are given in the appendix.
41 citations
TL;DR: An efficient algorithm for maximum-likelihood decoding of Raptor codes used over the binary erasure channel is proposed and is an improved version of the 3GPP multimedia broadcast/multicast services standard.
Abstract: In this letter, we propose an efficient algorithm for maximum-likelihood decoding of Raptor codes used over the binary erasure channel. The algorithm is inspired by the decoding scheme suggested in the 3GPP multimedia broadcast/multicast services standard and is an improved version of it.
41 citations
19 Apr 2015
TL;DR: In this work, aiming at a low-latency list decoding implementation, a double thresholding algorithm is proposed for a fast list pruning and, with a negligible performance degradation, the list pruned delay is greatly reduced.
Abstract: For polar codes with short-to-medium code length, list successive cancellation decoding is used to achieve a good error-correcting performance. However, list pruning in the current list decoding is based on the sorting strategy and its timing complexity is high. This results in a long decoding latency for large list size. In this work, aiming at a low-latency list decoding implementation, a double thresholding algorithm is proposed for a fast list pruning. As a result, with a negligible performance degradation, the list pruning delay is greatly reduced. Based on the double thresholding, a low-latency list decoding architecture is proposed and implemented using a UMC 90nm CMOS technology. Synthesis results show that, even for a large list size of 16, the proposed low-latency architecture achieves a decoding throughput of 220 Mbps at a frequency of 641 MHz.
41 citations
TL;DR: This article presents an algorithmic improvement to Sudan's list-decoding algorithm for Reed-Solomon codes and its generalization to algebraic-geometric codes from Shokrollahi and Wasserman by computing sufficiently many coefficients of a Hensel development to reconstruct the functions that correspond to codewords.
Abstract: This article presents an algorithmic improvement to Sudan's (see J. Complexity, vol.13, p.180-93, 1997) list-decoding algorithm for Reed-Solomon codes and its generalization to algebraic-geometric codes from Shokrollahi and Wasserman (see ibid., vol.45, p.432-37, 1999). Instead of completely factoring the interpolation polynomial over the function field of the curve, we compute sufficiently many coefficients of a Hensel development to reconstruct the functions that correspond to codewords. We prove that these Hensel developments can be found efficiently using Newton's method. We also describe the algorithm in the special case of Reed-Solomon codes.
41 citations
TL;DR: The increased interference-rejection capability that can be obtained from convolutional coding with Viterbi decoding, Reed-Solomon coding with errors-and-erasures decoding, and block product coding with iterative decoding is explored.
Abstract: High-rate direct-sequence spread spectrum is a modulation technique in which most or all of the spreading is provided by nonbinary data modulation. For applications to mobile ad hoc wireless networks, the limited processing gain of high-rate direct-sequence spread spectrum gives only modest protection against multiple access or multipath interference, which limits the applicability of the modulation technique to fairly benign channels. In this paper, we explore the increased interference-rejection capability that can be obtained from convolutional coding with Viterbi decoding, Reed-Solomon coding with errors-and-erasures decoding, and block product coding with iterative decoding. For channels with multiple access or multipath interference, performance results are given for several soft-decision decoding metrics, the benefits of adaptive-rate coding are illustrated, and the accuracy and utility of the Gaussian approximation are described. We also show how to use the bit-error probability for a system without error-control coding to determine which modulation method will give the best packet-error probability in a system with error-control coding
41 citations