An Identification Algorithm for LDPC Codes Using Maximum Deviation Ratio

With the extensive application of adaptive modulation and coding techniques (AMC) and low density parity codes (LDPC), identification technology for LDPC in AMC has drawn more and more researchers’ attention. For that problem, the existing methods have been suffering weak identification performance, so this paper presents a new recognition algorithm for LDPC in AMC based on maximum deviation ratio. First, the paper defines the log-likelihood ratio (PLLR) of the parity relationship with the soft-decision sequence, and makes some necessary analysis on its module value’s probability distribution. Then, using the statistical differences of the parity log-likelihood ratio on the various parity check matrix, a maximum deviation ratio based decision device is proposed, which takes into account both mean and variation properties of PLLR. Simulation results show that the new recognition algorithm can effectively identify the LDPC codes in AMC, even in the low signal-to-noise ratio channel environments. Especially for the high code rate LDPC codes, the new algorithm is better than existing ones.