LAUSR

Channel estimation for multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) systems is a challenging issue in high mobility scenarios due to prohibitive pilot overhead and complexity. In this paper, a hierarchical basis expansion model (BEM) based channel estimation scheme is proposed for doubly selective channels, which requires a low pilot overhead and computational complexity. A mixed-BEM is proposed for time-varying channels alongside a complex exponential-BEM (CE-BEM), resulting in very few unknown parameters required for channel estimation. Based on the hierarchical BEM structure, an analytical channel estimation model is derived. By employing the block-structured sparsity and a small number of mixed-BEM coefficients in the antenna-time-BEM domain, a low-complexity estimator is proposed to recover the mixed-BEM coefficients accurately. The lower bound on the mean square error (MSE) of channel estimation is derived to verify the effectiveness of the proposed scheme. Simulation results show that the proposed channel estimation scheme significantly outperforms the existing methods in terms of MSE of channel estimation and bit error rate, with much lower pilot overhead and computational complexity.