Blind Estimation of Frequency Features from Telecommunication Signals Using Modified Time Smoothing Algorithm

Cyclostationary Feature Detection has the ability to separate the signal or interest from noise and /or interference, but the computational complexity of cyclic Spectral analysis limits its use as a signal analysis tool. To reduce the computational complexity of cyclic Spectral analysis, this paper proposes Strip Spectral Correlation Algorithm (SSCA) to estimate carrier frequency and symbol rate. The simulation results show that the estimation values are still accurate when the SNR is low.