Sparsity-Aware Direct Equalization of Time-Varying Channels for V2V Communications

In this letter, we propose a new adaptive anti-interference equalization technique for fast time-varying channels. The equalization is implemented by basis expansion model (BEM) based time-varying (TV) finite impulse response (FIR) filters. By exploiting the sparsity of angle of arrival, we propose the idea of adaptive basis expansion for direct equalization. The optimization problem of the basis functions is formulated and solved by block orthogonal matching pursuit (BOMP) algorithm. We further propose a decision directed solution to improve the equalization performance. Simulation results show that the proposed methods exhibit a significant gain over conventional schemes.