Recursive least-squares decision-directed tracking of doubly-selective channels using exponential basis models

We present a decision-directed tracking approach to doubly-selective channel estimation exploiting the complex exponential basis expansion model (CE-BEM). 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 those of the channel. We track the BEM coefficients via the exponentially-weighted recursive least-squares (RLS) algorithm, aided by symbol decisions from a decision-feedback equalizer (DFE). Simulation examples demonstrate its superior performance over an existing subblock-wise channel tracking scheme.