MA-Aided Integrated Sensing and Covert Communication Systems

In contrast to conventional fixed-position antennas (FPAs), movable antennas (MAs) are capable of actively exploiting the spatial channel variations to enhance the performance of wireless systems. In this paper, we investigate a movable antenna (MA) aided integrated sensing and covert communication (ISACC) system, where the MA movable regions are quantized into practical discrete positions. We aim to maximize the covert sum rate by jointly optimizing the BS transmit beamformers, the positions of both BS- and user-side MAs, and the radar receive equalizer, subject to constraints on radar echo signal-to-clutter-plus-noise ratio (SCNR) and covertness. To effectively tackle this problem, an efficient successive convex approximation (SCA) based alternating optimization (AO) algorithm is proposed, where the complicated log-fractional objective function is handled by fractional programming (FP) technique, and the discrete MA position variables are optimized by employing the penalty strategy. To obtain useful insights, we then focus on a simple single-user single-target (SUST) scenario, and demonstrate that the optimal Tx MA positions aim to de-correlate the BS-target and BS-Willie channels, whereas the optimal Tx MA positions can be flexibly chosen. Furthermore, we extend our work into the practical imperfect CSI scenario, in which a conservative approximation of the covertness constraint is derived, based on which the proposed AO algorithm is still applicable after some slight modifications. Numerical results demonstrate the superior performance of our proposed algorithms under both perfect CSI and imperfect CSI.