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

Abstract

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 de-coding performance of GA-MP algorithm can achieve perfor-mances very close to the algorithm, while outperform MP algo-rithm. Besides, its performance will grow proportionally with the generation number without leveling off as observed in conven-tional MP algorithms, under high SNR condition.