A new approach based on "soft statistics" to the nonlinear blind-deconvolution of unknown data channels

In this paper, we present a new nonlinear receiver for the blind deconvolut ion of intersymbol interference (SI) impaired data, The proposed receiver a chieves fast identification of an unknown transmission channel using only o ne channel estimator and requiring the computation of only the second-order conditional statistics of the baud-rate sampled received signal and the kn owledge of the transmitted constellation, The main novelty of the proposed approach is that the receiver accomplishes fast channel-identification by u sing soft-statistics. In particular, the receiver consists of a symbol-by-s ymbol maximum a posteriori (SbS-MAP) detector that feeds a nonlinear Kalman -like channel estimator with the soft statistics constituted by the a poste riori probabilities (APPs) of the state sequence of the ISI channel, Severa l numerical results confirm that the proposed blind detector achieves the i dentification of nonminimum phase channels with deep spectral notches withi n 300 symbols, even at low signal-to-noise ratios (SNRs). Furthermore, an a ttractive feature of the proposed blind channel estimator is that it direct ly estimates the discrete-time impulse response of the unknown channel so t hat, in principle, any equalization technique for known channels may be per formed after channel identification has been achieved.