Iterative SNR Estimation Algorithm for M-APSK Signal Based on A Priori Information
基于先验信息的M-APSK信号迭代信噪比估计

This paper proposes an iterative Signal-to-Noise Ratio (SNR) estimation algorithm suited to Multiple Amplitude Phase Shift Keying (M-APSK) signal based on a priori information. Given a priori, the M-PASK signal has the determinate probability distribution with flat-fading, and its logarithmic expection is differentiated to yield the relation between the SNR parameters and the data. Reliability metric is introduced to updata the parameters, then the iterative algorithm is put forward correspondingly. Compared with the foregone Memont Methods (MM), simulation results show that the new algorithm using a prior has better performance when the intrinsic information is larger than 0.4 with 4 iterations, while that without a prior only better in middle and hign SNR with 5 iterations used.