Open AccessEfficient Information Set Decoding Based on Genetic Algorithms
Author(s) -
Ahmed Azouaoui,
Idriss Chana,
Mostafa Belkasmi
Publication year - 2012
Publication title -
international journal of communications, network and system sciences/international journal of communications, network, and system sciences
Language(s) - English
Resource type - Journals
eISSN - 1913-3723
pISSN - 1913-3715
DOI - 10.4236/ijcns.2012.57052
Subject(s) - decoding methods , algorithm , computer science , berlekamp–welch algorithm , set (abstract data type) , sequential decoding , binary number , list decoding , theoretical computer science , block code , mathematics , concatenated error correction code , arithmetic , programming language
In this paper, we describe a hard-decision decoding technique based on Genetic Algorithms (HDGA), which is applicable to the general case of error correcting codes where the only known structure is given by the generating matrix G. Then we present a new soft-decision decoding based on HDGA and the Chase algorithm (SDGA). The performance of some binary and non-binary Linear Block Codes are given for HDGA and SDGA over Gaussian and Rayleigh channels. The performances show that the HDGA decoder has the same performances as the Berlekamp-Massey Algorithm (BMA) in various transmission channels. On the other hand, the performances of SDGA are equivalent to soft-decision decoding using Chase algorithm and BMA (Chase-BMA). The complexity of decoders proposed is also discussed and compared to those of other decoders