Fast Convergence Algorithm for Blind Channel Estimation and Equalization Using CMF-DFE

A novel fast blind equalizer is obtained by using the direct calculations from a channel matched filter decision feedback equalizer (CMF-DFE). The proposed technique converts the inverse convolution operations of an equalizer into a linear finite impulse response estimation filter, which is more suitable for blind training. A novel error function is introduced for blind training which enables the use of fast algorithms such as LMS or RLS. The required auto-regression values for the CMF-DFE equalizer are calculated from the incoming data. The resulting performance with LMS training is close to that of non-blind techniques.