Blind channel identification and optimal MMSE equalization using nonmaximally decimated multirate filterbank based precoder/post-equalizer

A novel nonmaximally decimated multirate fllterbank structure is proposed for blind identification of communication channels. This structure is shown to be very similar to a form proposed earlier in the literature. It is shown that the proposed blind channel identification algorithm is not sensitive to the characteristics of the unknown channel, including mixed phase and zeros on the unit circle. An optimal minimum mean square error-based linear equalizer using the blind channel identification scheme is investigated. It is shown that the proposed system outperforms the existing zero-forcing blind equalization algorithms in the literature. It can simultaneously cancel the intersymbol interference (ISI) and suppress the noise enhancement. The reconstructed signal-to-noise ratio is maximized by the proposed algorithm. Simulation results show the superior performance and robustness of the proposed blind identification and equalization scheme.