A Novel Blind SNR Estimator Based on the Modified PASTd Algorithm for IF Signals

Abstract

A blind Signal-to-Noise Ratio (SNR) estimator based on the modified Projection Approximation Subspace Tracking deflation (PASTd) algorithm is proposed in this paper for Intermediate Frequency (IF) signals in the complex additive white Gaussian noise (AWGN) channel. Compared with the eigenvalue decomposition (ED)-based method, the proposed algorithm can achieve a more accurate estimation with a simple computational complexity. Simulations are performed for the commonly used IF signals. The results show that the performance of the algorithm is robust and when the true SNR is in the range from 5dB to 25dB the estimation bias is under 1dB and the corresponding standard deviation (STD) is within 0.3.