A Genetic-algorithm Based Decoder for Low Density Parity Check Codes

This paper presents a GeneticAlgorithm based decoder for a medium-sized Low Density Parity Check code (GAMD decoder). The main advantage of the proposed GAMD decoder is that no information on the noise level transmission channel is required, an essential condition for the well-known sum product algorithm. The proposed methodology combines a Genetic Algorithm stage with a meta-decision process. Genetic Algorithms were selected due to their capacity to solve this type of multiple minimum. Encouraging results were reached when comparing the Bit Error Rate (BER) performance of the proposed algorithm with that of the traditional sum-product decoding algorithm. The performance of the proposed decoder is very close to that of the optimal sum-product decoder, with the additional benefit of not requiring channel information (signal-to-noise ratio). In order to improve Bit Error Rate performance and/or reduce the complexity of the proposed decoder, the fitness function and parameters of the GA can be optimized. Keywords— LDPC codes, Genetic Algorithm, Sum-product Algorithm.