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Soft decision decoding of linear block codes using genetic algorithms

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4 Author(s)
Maini, H. ; Sch. of Comput. & Inf. Sci., Syracuse Univ., NY, USA ; Mehrotra, K. ; Mohan, C. ; Ranka, S.

Soft decision decoding is a difficult search problem, for which optimal algorithms are computationally intractable. Genetic algorithms (GA) are stochastic optimisation techniques that have successfully solved many difficult search problems. We have developed a high performance GA for suboptimal soft decision decoding of binary linear block codes, which gives bit error probabilities as low as 0.00183 for a [104, 52] extended quadratic residue code with a signal-to-noise ratio of 2.5 dB, exploring only 30,000 codewords, whereas the search space contains 1015 codewords. Success ensues from the use of a new crossover operator that exploits problem-specific knowledge

Published in:

Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on

Date of Conference:

27 Jun-1 Jul 1994

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