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


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 = 105 with only 4 processors.

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A. Ahmadi, F. El Bouanani, H. Ben-Azza and Y. Benghabrit, "A Novel Decoder Based on Parallel Genetic Algorithms for Linear Block Codes," International Journal of Communications, Network and System Sciences, Vol. 6 No. 1, 2013, pp. 66-76. doi: 10.4236/ijcns.2013.61008.

Conflicts of Interest

The authors declare no conflicts of interest.


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