Channel Estimation for Movable Antenna Communication Systems Based on Compressed Sensing

This paper proposes a general channel estimation framework for movable antenna (MA) communication systems. In this framework, the channel state information between the entire transmitter (Tx) and receive (Rx) regions can be re-constructed, so as to find the optimal positions of the MAs for reaping performance gains. Specifically, the field-response channel structure is utilized to represent the channel response in terms of the angles of departure (AoDs), angles of arrival (AoAs), and complex coefficients of the multi-path components (MPCs). Then, the compressed sensing method is employed to jointly estimate the MPC information, i.e., the AoDs, AoAs, and complex coefficients of the paths, with a limited number of channel measurements. Notably, the measurement matrix under the proposed framework is fundamentally determined by the Tx-MA and Rx-MA measurement positions, which further affects the channel estimation performance. In this regard, four MA measurement position setups are proposed, and the channel estimation performance of each setup is further compared. Finally, simulation results show that the complete CSI between the entire Tx and Rx regions can be reconstructed by our proposed channel estimation framework with a high accuracy.