Data Detection for Doubly-Selective MIMO Channels Using Decision-Directed Channel Tracking and Exponential Basis Models

We present a decision-directed tracking approach to doubly-selective MIMO channel estimation, exploiting the complex exponential basis expansion model (CE-BEM) for the overall channel variations, and an autoregressive (AR) model to update the BEM coefficients. We track the BEM coefficients via Kalman filtering, aided by symbol decisions from a decision-feedback equalizer (DFE). The time gap between symbol decisions and required channel estimates, arising from the decision-directed tracking, is bridged by CE-BEM-based channel prediction using the estimated BEM coefficients. Simulation examples demonstrate its superior performance over the existing AR-based and subblock-wise channel tracking schemes.