Movable Antenna-Assisted Integrated Sensing, Communication, and Computation Over-the-Air: Joint Beamforming and Antenna Position Design

Integrated sensing, communication, and computation over-the-air (ISCCO) is a promising framework for sup porting massive Internet of Things (IoT) applications by unifying radar sensing, data transmission, and over-the-air computation (AirComp). This paper proposes a movable antenna (MA) assisted ISCCO system, where the access point (AP) and in tegrated sensing and communication (ISAC) sensors employ MA arrays to improve channel conditions. We formulate a joint optimization problem of transceiver beamforming and antenna positions to minimize the AirComp mean squared error (MSE), subject to constraints on the sensing Cram´ er-Rao bound (CRB), transmit power, and antenna positions. To address the non-convex problem, we develop a block coordinate descent (BCD)-based algorithm using approximate convex optimization techniques. Numerical results demonstrate that the proposed algorithm achieves low computational complexity and significantly reduces AirComp MSE compared to fixed-antenna schemes.