期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2018
卷号：96
期号：13
出版社：Journal of Theoretical and Applied
摘要：The general problem of soft-decision decoding a linear code is a NP-complete problem. This article introduces a soft-decision decoding algorithm, the first of its kind, based on memetic algorithm. The new approach is applicable to the more general case of linear codes; binary or nonbinary codes and cyclic and noncyclic codes where the only known structure is given by the generator matrix. The proposed algorithm used in each generation, two individuals selected randomly; the uniform crossing that exploits information specific to the communication system; a mutation that simply involves altering one or more genes in an individual and a local search (LS) that makes a descent by glorifying the created individual. The proposed decoder is simulated in an AWGN channel and enhanced through a parameter tuning process. In other side the simulation results generally show that our decoder is more efficient in terms of bit error rate compared to competitors' decoding algorithms. The analytical complexity of the proposed decoder is also presented and compared to other decoders.
