This paper presents a novel genetic algorithm for jointly optimizing source and channel codes. The algorithm uses a channel-optimized vector quantizer for the source code, and a rate-punctured convolutional code for the channel code. The genetic algorithm enhances the robustness of the rate-distortion performance of the channel-optimized vector quantizer, and reduces the computational time for finding the best rate-punctured convolutional code. Numerical results show that the algorithm attains near optimal performance while having low computational complexity. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Ou, C. M., Hwang, W. J., & Yung, H. C. (2006). Design of robust communication systems using genetic algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3905 LNCS, pp. 270–279). https://doi.org/10.1007/11729976_24
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