Fast blind equalization using higher-order-spectra channel-estimation in the presence of severe ISI

The blind equalization of data distorted in dispersive channels with considerable ISI is investigated. The blind channel estimation is realized without using training sequences. Two methods based on the higher order spectra and polycepstra are considered. The estimated channel response is used to adaptively equalize the distorted data. The speed of convergence of the adaptive equalizer is highly increased by suitable filtration of the estimated channel impulse response before adaptive equalization. This is done by providing smart initial weights for the adaptive equalizer through inverse filtering or matched filtering of the estimated channel response. The addition of a deconvolving filter to the matched filter is suggested to cancel the effects of the high offset correlation values of the channel impulse response that is characteristic of channels with severe ISI.