Doubly-selective mimo channel estimation using exponential basis models and subblock tracking

We present a subblock-wise tracking approach to doubly-selective MIMO channel estimation, exploiting the oversampled complex exponential basis expansion model (CE-BEM) for the overall channel variations, and an autoregressive (AR) model to update 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 track the BEM coefficients via Kalman filtering, based on time-multiplexed periodically transmitted training symbols. Simulation examples demonstrate its superior performance over some existing doubly-selective channel tracking schemes.