Document Type





Genetic algorithms, Soft-decision decoding, Uniform crossover




Computer Sciences


Soft-decision decoding is an NP-hard problem of great interest to developers of communication systems. We show that this problem is equivalent to the problem of optimizing Walsh polynomials. We present genetic algorithms for soft-decision decoding of binary linear block codes and compare the performance with various other decoding algorithms including the currently developed A* algorithm. Simulation results show that our algorithms achieve bit-error-probabilities as low as 0:00183 for a [104; 52] code with a low signal-to-noise ratio of 2:5 dB, exploring only 22; 400 code words, whereas the search space contains 4:5 \Theta 10 15 codewords. We define a new crossover operator that exploits domain-specific information and compare it with uniform and two point crossover. Keywords: genetic algorithms, soft-decision decoding, uniform crossover.

Creative Commons License

Creative Commons Attribution 3.0 License
This work is licensed under a Creative Commons Attribution 3.0 License.



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