Blind recognition of sparse parity‐check matrices of low‐density parity‐check codes in the presence of noise
Yong Ding, Zhiping Huang, Jing Zhou · IET Communications · 2022
Abstract This paper studies the blind recognition method of the sparse parity‐check matrices of low‐density parity‐check codes in noncooperative communication, which is critical to the reverse analysis of communication protocols using LDPC codes. In this paper, two improvements are made to the algorithm of Liu Qian et al. (2021) for this problem. Firstly, a Gaussian elimination method based on random column exchange and soft information is proposed to enhance the fault tolerance of the elimination process. Secondly, according to the sparse property of the parity‐check matrices of LDPC codes, a random extraction method is proposed to further improve the fault tolerance of the algorithm, and it is verified theoretically. Finally, simulations verify the superior performance of the algorithm proposed in this paper.