TLS blind recognition algorithm of LDPC codes

Blind recognition of low-density parity-check (LDPC) codes has gradually attracted more attention with the development of military and civil communications. However, in the case of the parity-check matrices with relatively high row weights, the existing blind recognition algorithms based on a candidate set generally perform worse. In this paper, we propose a blind recognition method for LDPC codes, called as tangent function assisted least square (TLS) method, which improves recognition performances by constructing a new cost function. To characterize the constraint degree among received vectors and parity-check vectors, a feature function based on tangent function is constructed in the proposed algorithm. A cost function based on least square method is also established according to the feature function values satisfying the parity-check relationship. Moreover, the minimum average value in TLS is obtained on the candidate set. Numerical analysis and simulation results show that recognition performances of TLS algorithm are consistent with theoretical results. Compared with existing algorithms, the proposed method possesses better recognition performances.