Decoding algorithm of LDPC codes based on genetic algorithm

In order to improve the decoding performance of low density parity check (LDPC) codes, a sum-product genetic decoding (SPGD) algorithm based on genetic algorithm (GA) is proposed. By means of the classical decoding algorithm of sum-product algorithm (SPA) of LDPC codes, variable node information generated by each hard decision of iteration is regarded as individuals that constitute initial population of GA. The decoded optimal solutions are produced by a series of genetic operations. Simulation results show that under the premise of almost no increase in complexity, the proposed SPGD algorithm has the superior decoding error correction performance, better practicability and higher net coding gain (NCG).