基于改进平衡优化算法的LDPC多参数译码算法OA

Low-density parity-check(LDPC)codes have emerged as a prominent research focus in the field of information and coding theory due to their exceptional error correction performance,which approaches the Shannon limit.To optimize the parameters of the LDPC decoding algorithm,an improved multi-parameter joint optimization framework for LDPC decoding based on the enhanced equilibrium optimizer(IEO)was proposed,denoted as improved EO optimized multi parameters decoding(IEO-MPDA)algorithm.The framework was developed by integrating the layered normalized min-sum algorithm(LNMSA)with the layered offset min-sum algorithm(LOMSA),effectively expanding the parameter search space from one-dimensional to two-dimensional and thereby increasing the degrees of freedom in parameter optimization.Furthermore,an adaptive stagnation detection mechanism,dynamic exponential weighted balance pool construction,elite individual crossover and mutation operations,and Latin hypercube initialization method were introduced,successfully addressing the issue of traditional EO algorithms tending to converge to local optima when solving decoding parameter optimization problems.Simulation results demonstrate that IEO-MPDA achieves superior decoding performance improvement of approximately 0.2 dB compared to existing traditional parameter decoding optimization schemes,without incurring additional decoding complexity.