On blind identification of S.I.M.O. time-varying channels using second-order statistics

Blind estimation of SIMO (single-input multiple-output) rapidly time-varying communications channels is considered using only the second-order statistics of the data. The time-varying channel is assumed to be described by a complex exponential basis expansion model (CE-BEM). The linear prediction error method for blind estimation of time-invariant channels is extended to time-varying channels represented by a CE-BEM. Sufficient conditions for identifiability/equalizability are investigated. The cyclostationary nature of the received signal is exploited to consistently estimate the time-varying correlation function of the data from a single observation record. A simulation example is presented to illustrate the proposed approach.