Efficient Genetic Algorithm-based LDPC Code Design for IoT Applications

In this paper, we propose an improved Low-Density Parity-Check (LDPC) code design scheme based on the existing genetic optimization-based LDPC code design scheme proposed in [1]. In particular, we perform the removal of the girth-4 property of the parity check matrix (H-matrix) and utilize the min-sum decoding algorithm instead of the Belief Propagation (BP) algorithm in order to enhance the performance of the LDPC code. Furthermore, an (32,64) LDPC code is considered in this paper. Finally, we evaluate the block error rate (BLER) of the LDPC code over white Gaussian noise channels. By means of evaluation results using Matlab, we indicate that our proposed approach can achieve a gain of more than 11% in terms of BLER compared to the existing schemes without significantly increasing the complexity of the decoding scheme.