Compressive Sensing Based UAV Communication and Sensing MIMO System with Movable Antenna

This paper investigates the application of movable antenna-based integrated sensing and communication (MA-ISAC) in millimeter-wave (mmWave) massive multiple-input multiple-output (mMIMO)-enabled unmanned aerial vehicle (UAV) networks. Specifically, we propose a full duplex terrestrial station architecture that co-locates MA with uniform linear array (ULA), which can simultaneously communicate with UAV and sense the surrounding environment to avoid potential collision risks. To reduce pilot overhead required for channel estimation (CE) and radar sensing (RS), a state-of-the-art joint multi-domain (angle and delay domain) compressive sensing (JM-CS) scheme is applied to ISAC processing in UAV networks. On this basis, we also propose an adaptive optimal antenna movement (AOAM) strategy, this method leverages the channel angle and time-delay information acquired by JM-CS to compute the current channel, thus screening out the port with the highest signal power as the receiving port for the MA's next reception position. By continuously iterating this process, the impact of deep channel fading can be minimized, and further the CE accuracy and RS accuracy can be improved. Simulation results demonstrate the superior performance of CE and RS by leveraging the proposed AOAM strategy.