Blind parameters estimation by exploiting cyclostationary features in wavelet domain

Abstract

In dynamic environment, multi-standard wireless communication receivers capable of estimating the various parameters of any unknown modulated signal are desired. These parameters include symbol rate, modulation type, carrier frequency etc. For identifying the modulation type, symbol rate estimation is primary step while carrier frequency estimation is useful when there is relative motion between transmitter and receiver. Accurate estimation of these parameters is the objective of the work presented in this thesis. The first contribution of the thesis is symbol rate estimation and modulation classifier. The proposed method exploits cyclostationary features of the received signal in wavelet domain. Simulation results for AWGN and Rayleigh fading channel shows the superiority of the proposed approach over existing approaches especially at low SNRs. The proposed method then extended to the automatic modulation classification and estimation of carrier frequency. At the end, detailed complexity analysis based on total number of gate counts is presented.