Symbol rate estimation of PSK signals under cyclostationary framework based on compressing transform function in alpha-stable noise

A novel compressing transform (CT) function based cyclic autocorrelation (CTCA) under the cyclostationary framework is presented, which is intended for the symbol rate estimation of phase-shift keying (PSK) signals in the presence of alpha-stable noise. The domain of the CT function built in this paper can be divided into the approximate linear zone (ALZ) and the suppression zone (SZ). The ALZ helps the proposed CT function keep the useful information of signals-of-interest unchanged and because of the SZ, the CT function can mitigate effectively the large amplitudes of the impulsive noise. Subsequently, motivated by the excellent parameter estimation performance of the cyclic autocorrelation and based on the constructed CT function, the CTCA is proposed for symbol rate estimation in alpha-stable noise. Afterwards, the estimation accuracy of the proposed CTCA is measured by the normalized root mean square error in Monte Carlo simulations. According to the simulation results, the proposed method is feasible for PSK symbol rate estimation, and it distinctively outperforms the equivalent cyclic autocorrelation based counterparts especially in a strong impulsive noise environment. (C) 2021 Elsevier Inc. All rights reserved.