Blind Recognition of LDPC Codes Over Candidate Set

Adaptive modulation and coding (AMC) techniques have attracted more attention recently because of flexible strategies and dynamic channel quality. Blind recognition of encoder is an important technology for AMC systems because it can improve communication efficiency very well. In this letter, we present a new algorithm to tackle blind low-density parity-check (LDPC) encoder identification over a given candidate set. Our proposed scheme establishes a cosine conformity (CC) of syndrome, which is a posterior probability that can measure the probability that all parity check relations of the codes are satisfied, and classifies the LDPC encoder leading to maximum average CC over the candidate set. Simulations show that the new method is effective for LDPC encoder identification; the theoretical correct ratio of recognition is consistent with the simulation results, and its performance is improved by nearly 1.5 dB when compared with the existing algorithm.