Robustness of blind fractionally-spaced identification/equalization to loss of channel disparity

We address the comparison of sub-space (SS), linear prediction (LP) and constant modulus (CM) identification/equalization algorithms in terms of robustness to loss of fractionally-spaced channel disparity. We show that SS procedure leads to an inconsistent channel estimation. Investigating a left-inverse channel estimation, we show that LP results in the estimation of the so-called minimum-phase multivariate channel factorization. We show that the CM criterion still perform reasonable channel estimation, even if proper algorithm initialization is still a critical subject