• DocumentCode
    2786638
  • Title

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

  • Author

    Jui-Hui Hung ; Yi-De Lu ; Sau-Gee Chen

  • Author_Institution
    Dept. of Electron. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
  • fYear
    2012
  • fDate
    3-6 Sept. 2012
  • Firstpage
    1
  • Lastpage
    5
  • 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 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.
  • Keywords
    communication complexity; genetic algorithms; maximum likelihood decoding; message passing; parity check codes; GA-MP algorithm; LDPC codes; LDPC decoding algorithm; ML decoding algorithm; SNR condition; computational complexity; decoding performance; genetics-aided message passing decoding algorithm; maximum likelihood decoding algorithm; Approximation algorithms; Genetic algorithms; Iterative decoding; Maximum likelihood decoding; Reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicular Technology Conference (VTC Fall), 2012 IEEE
  • Conference_Location
    Quebec City, QC
  • ISSN
    1090-3038
  • Print_ISBN
    978-1-4673-1880-8
  • Electronic_ISBN
    1090-3038
  • Type

    conf

  • DOI
    10.1109/VTCFall.2012.6399254
  • Filename
    6399254