Adaptive Smooth-Windowed Wigner-Ville Distribution for Digital Communication Signal

Time-frequency distributions (TFD's) are powerful tools to represent the energy content of time-varying signal in both time and frequency domain simultaneously but it suffers from interference due to cross terms. Various methods have been described to remove these cross-terms and typically signal dependent. Thus, there is no single TFD with a fixed window or kernel that produce accurate time-frequency representation (TFR) for all type of signals. In this paper, an adaptive smooth-windowed Wigner-Ville distribution (SWWVD) is designed for digital modulation signals such as ASK, FSK and M-ary FSK where its separable kernel parameters are determined automatically from the parameters of the input signal. This optimum kernel is capable to remove the cross-terms and maintain accurate time-frequency representation. Compared with kernel parameters derived mathematically, it is shown that the adaptive SWWVD gave similar accuracy in the time-frequency representation.