Wavelet denoising spproach using fourth order moment to remove wireless random noise

Wavelet transform is used in signal processing to represent a statistical random signal in to various frequency components. The transform converts the signal into approximation coefficient and detail coefficients; the mean of each coefficient for a noiseless signal is ideally zero but the mean of the coefficients for a noisy signal is shifted from zero. The noise of a wireless channel can be reduced by using filter, equalizer, and antennal diversity techniques. The design complexity of filter and equalizer is increased with the data rate. Antenna diversity technique requires a comprehensive knowledge of channel property. In communication system of 3G, 4G and beyond, noise reduction is one of the main factors to cater for the high data rate. The thresholding of wavelet transform reduces the noise and interference at an acceptable level. Various denoising techniques have been proposed in recent work. The denoising approach using fourth order moments provides better signal reconstruction through a noisy channl among them. Fourth order moment-based denoising technique has been modified in this paper to obtain better result through a multipath fading channel. The simulation results show that our modified technique provides about 21% improvement of BER performance, compared to those in the literature.