A Two-Stage Maximum a Posterior Probability Method for Blind Identification of LDPC Codes

Abstract

Blind identification of encoders has received increasing attention in recent years. In this letter, we focus on LDPC coded communication systems and study the problem of blind identification over a candidate set. We propose a blind identification method based on a two-stage maximum a posteriori probability estimation. The first stage measures the parity-check relationship between the received vectors and the rows of the parity-check matrices in the candidate set, and the second stage deals with the effect of row weights. Moreover, We theoretically explained the mechanism by which row weight affects identification results and proved that the proposed method can considerably suppress the preference of the existing methods for low row weights. Simulation results show that the proposed method always has a higher probability of correct identification for parity-check matrices with high row weights in the candidate set than the existing methods.