A New Genetics-Aided Message Passing Decoding Algorithm for LDPC Codes

The popular LDPC decoding algorithms based on the message passing (MP) algorithm have high decoding performances. However, they are noticeably inferior to the maximum likelihood (ML) decoding algorithm. This work proposes a genetics-aided message passing (GA-MP) algorithm by applying a new genetic a...

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Bibliographic Details
Published in:2012 IEEE Vehicular Technology Conference (VTC Fall) pp. 1 - 5
Main Authors: Jui-Hui Hung, Yi-De Lu, Sau-Gee Chen
Format: Conference Proceeding
Language:English
Published: IEEE 01.09.2012
Subjects:
Approximation algorithms
Genetic algorithms
Iterative decoding
Maximum likelihood decoding
Reliability
ISBN:1467318809, 9781467318808
ISSN:1090-3038
Online Access:Get full text
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Summary:The popular LDPC decoding algorithms based on the message passing (MP) algorithm have high decoding performances. However, they are noticeably inferior to the maximum likelihood (ML) decoding algorithm. This work proposes a genetics-aided message passing (GA-MP) algorithm by applying a new genetic algorithm to MP algorithm. As a result, significantly performance improvement over MP algorithm can be achieved. Besides, compared with other genetic-aided decoding algorithms, the proposed algorithm has much better performances and much lower computational complexity. Simulations show that the decoding performance of GA-MP algorithm can achieve performances very close to the algorithm, while outperform MP algorithm. Besides, its performance will grow proportionally with the generation number without leveling off as observed in conventional MP algorithms, under high SNR condition.
ISBN:1467318809
9781467318808
ISSN:1090-3038
DOI:10.1109/VTCFall.2012.6399254