Closed Set Identification of LDPC Codes Based on Maximum Cosine Ratio

In order to improve the performance of LDPC code closed-set recognition with low signal-to-noise ratio, this paper proposes a soft decision recognition algorithm based on maximum cosine ratio. Based on the analysis of the problems of the maximum mean likelihood ratio algorithm, the algorithm uses the coding structure characteristics of the LDPC code to reduce the recognition process to the detection problem of the linear relationship in the binary domain; At the same time, a cosine test function that can effectively characterize the possibility of the establishment of linear coding constraints is introduced, based on the fact that the statistical characteristics of the cosine test function under the correct check matrix and the error check matrix are different, and use the cosine ratio in both cases as the basis for encoder determination, thereby achieving low signal-to-noise ratio effective identification of closed sets of LDPC codes. The simulation results show that the algorithm can reliably identify the commonly used LDPC codes in IEEE802.16e protocol under the condition of 0dB signal-to-noise ratio. At the same time, the performance of the algorithm is improved by nearly 1dB compared with the existing algorithm.