Blind Parameter Estimation of M-FSK Signals in the Presence of Alpha-Stable Noise

Abstract

Blind estimation of parameters for ${M}$ -ary frequency-shift-keying ( ${M}$ -FSK) signals is great of importance in intelligent receivers. Many existing algorithms have assumed white Gaussian noise. However, their performance severely degrades when grossly corrupted data, i.e., outliers, exist. This article solves this issue by developing a novel approach for parameter estimation of ${M}$ -FSK signals in the presence of alpha-stable noise. Specifically, the proposed method exploits the generalized first- and second-order cyclostationarity of ${M}$ -FSK signals with alpha-stable noise, which results in closed-form solutions for unknown parameters in both time and frequency domains. As a merit, it is computationally efficient and thus can be used for signal preprocessing, symbol timing estimation, signal and noise power estimation. Furthermore, substantial theoretical analysis on the performance of the proposed approach is provided. Simulations demonstrate that the proposed method is robust to alpha-stable noise and that it outperforms the state-of-the-art algorithms in many challenging scenarios.