Robust Beamforming and Antenna Position Optimization for MA-Assisted ISAC with Imperfectly Positioned MAs
This paper investigates robust beamforming and antenna position design for movable antenna (MA)-enabled integrated sensing and communication (ISAC) systems under antenna position errors. In particular, deviations between the actual and nominal antenna positions in practical MA arrays are inevitable due to limited mechanical accuracy. Therefore, the conventional ISAC design based on nominal positions may suffer from substantial performance degradation. To address this issue, we consider a monostatic downlink MA-ISAC system in which each transmission frame consists of a low-power pilot and an ISAC payload. The target angle, reflection coefficient, and antenna position-error vector are jointly estimated based on these two observations, thereby enabling sensing with imperfectly known antenna positions. We derive the resulting angle Cramer-Rao bound (CRB) and formulate a problem that minimizes its worst-case value subject to each user's signal-to-interference-plus-noise ratio (SINR) requirement under all possible position errors. By exploiting a common phase-response decomposition, we obtain tractable reformulations and develop an alternating optimization (AO) algorithm for the beamforming vectors and nominal antenna positions. Numerical results demonstrate that, compared with conventional nominal-position designs, the proposed robust scheme achieves improved communication reliability while maintaining competitive sensing accuracy under practical antenna position uncertainty.