Blind identification of time-varying channels using multistep linear predictors

Blind channel estimation for single-input multiple-output (SIMO) time-varying 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 multistep linear predictors-based method for blind identification of time-invariant channels is extended to time-varying channels represented by a CE-BEM. Sufficient conditions for identifiability are investigated. Cyclostationarity of the received signal is exploited to consistently estimate the time-varying correlation function of the data from a single observation. record. An illustrative computer simulation example is presented.