An Improved A^ Decoding Algorithm With List Decoding

Comparing with hard decision decoding algorithms, soft decoding has a lower probability of bit error but a higher computational complexity. As a maximum-likelihood soft decoding method, the <inline-formula> <tex-math notation="LaTeX">A^{\ast } </tex-math></inline-formu...

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Bibliographic Details
Published in:IEEE access Vol. 6; pp. 46877 - 46885
Main Authors: Xu, Bin, Ying, Chenhao, Luo, Yuan
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.01.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
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Accuracy
Algorithms
Binary system
Block codes
Codes
Complexity
Computational complexity
Decoding
Error correcting coding
Error probability
Generators
Heuristic algorithms
list decoding
Maximum likelihood decoding
ISSN:2169-3536, 2169-3536
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Summary:Comparing with hard decision decoding algorithms, soft decoding has a lower probability of bit error but a higher computational complexity. As a maximum-likelihood soft decoding method, the <inline-formula> <tex-math notation="LaTeX">A^{\ast } </tex-math></inline-formula> algorithm is the most basic and widely used to minimize bit error probability. However, its average computational complexity strongly depends on a seed codeword and a heuristic function utilized during the decoding process. To efficiently reduce the computational complexity while maintaining the decoding accuracy theoretically and practically, this paper proposes an improved <inline-formula> <tex-math notation="LaTeX">A^{\ast } </tex-math></inline-formula> decoding algorithm consisting of two phases. The first phase applies the greedy list decoding to the linear block code to obtain a seed codeword. According to the seed, the second phase applies the improved <inline-formula> <tex-math notation="LaTeX">A^{\ast } </tex-math></inline-formula> algorithm to obtain the final decoding output. The heuristic function used in the <inline-formula> <tex-math notation="LaTeX">A^{\ast } </tex-math></inline-formula> algorithm is modified in two aspects: 1) use more information of partial decoded symbols to improve the accuracy of the function and 2) take advantage of Hamming distance to reduce the search space. Simulations on the <inline-formula> <tex-math notation="LaTeX">RM(5,2) </tex-math></inline-formula> Reed-Muller codes and [128, 64] binary extended BCH code show that this improved <inline-formula> <tex-math notation="LaTeX">A^{\ast } </tex-math></inline-formula> algorithm is more efficient in average decoding complexity than many other algorithms while maintaining the decoding accuracy.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2018.2866396