Recursive least-squares doubly-selective MIMO channel estimation using exponential basis models

Abstract

An adaptive MIMO channel estimation scheme, exploiting the oversampled complex exponential basis expansion model (CE-BEM), is presented for doubly-selective fading channels where we track the BEM coefficients. The time-varying nature of the channel is well captured by the CE-BEM while the time-variations of the (unknown) BEM coefficients are likely much slower than that of the channel. We apply the exponentially-weighted and sliding-window recursive least-squares (RLS) algorithms to track the BEM coefficients subblock-by-subblock, using time-multiplexed periodically transmitted training symbols. Simulation examples demonstrate its superior performance over the conventional block-wise channel estimator.