D. J. C. Mackay and R. M. Neal, “Good Codes Based on Very Sparse Matrices,” 5th IMA Conference on Cryptography and Coding. Lecture Notes in Computer Science number 1025, October 1995, Springer, Berlin, pp. 100-111. doi:10.1007/3-540-60693-9_13

has been cited by the following article:

• TITLE: A Novel Decoder Based on Parallel Genetic Algorithms for Linear Block Codes

  AUTHORS: Abdeslam Ahmadi, Faissal El Bouanani, Hussain Ben-Azza, Youssef Benghabrit

  KEYWORDS: Channel Coding; Linear Block Codes; Meta-Heuristics; Parallel Genetic Algorithms; Parallel Decoding Algorithms; Time Complexity; Flat Fading Channel; AWGN

  JOURNAL NAME: International Journal of Communications, Network and System Sciences, Vol.6 No.1, January 29, 2013

  ABSTRACT: Genetic algorithms offer very good performances for solving large optimization problems, especially in the domain of error-correcting codes. However, they have a major drawback related to the time complexity and memory occupation when running on a uniprocessor computer. This paper proposes a parallel decoder for linear block codes, using parallel genetic algorithms (PGA). The good performance and time complexity are confirmed by theoretical study and by simulations on BCH(63,30,14) codes over both AWGN and flat Rayleigh fading channels. The simulation results show that the coding gain between parallel and single genetic algorithm is about 0.7 dB at BER = 10﹣5 with only 4 processors.