Doubly selective channel estimation for MIMO systems based on structured compressive sensing

This paper proposes a novel doubly selective channel estimation scheme for MIMO-OFDM systems with both time- and frequency-domain training (TFDT) based on structured compressive sensing (SCS). The characteristics of the doubly selective channel is considered in three dimensions, i.e., sample-domain, tap-domain, and antenna-domain. The tap-domain channel impulse responses (CIRs) are jointly sparse, while the sample-domain CIRs can be expanded by specific bases. We utilize the received pseudo-random noise (PN) sequence to acquire the common support of the channel. After a cyclic reconstruction process, the channel estimation can be performed under an SCS model by exploiting the proposed pilot pattern and the spatial correlation among antennas. Simulation results demonstrate that the proposed scheme has a superior performance than that of conventional counterparts.