Robust Secure MIMO Integrated Sensing and Communications with Sensing-Assisted Wiretap Channel Awareness

A major limitation of physical layer security is the requirement for prior knowledge of the potential eavesdroppers' (Eves) channels, which makes its practical implementation challenging. Integrated sensing and communication systems can be exploited to address this issue by enabling both communication and sensing functionalities, sensing the physical environment to estimate Eves' directions and amplitudes, and further reconstructing their channel state information (CSI) to achieve sensing-assisted wiretap channel awareness, thus realizing secure communication. We analyze a more practical scenario where not only is reconstructed Eves' CSI inaccurate, but also the CSI of the legitimate user equipments (UEs) estimated by the base station is imperfect, and Eves are equipped with multiple antennas. To resolve this, we propose a robust optimization problem that jointly maximizes the sensing accuracy and the secrecy rate by co-designing the beamforming and the artificial noise matrix. For the highly challenging non-convex infinite objective function, the S-Procedure is introduced, which is then solved by an efficient algorithm based on alternating optimization and successive convex approximation. Numerical results validate the effectiveness of the proposed algorithm and demonstrate that the robust beamforming scheme can mitigate the impact of channel uncertainty (both UEs' and Eves') on the system performance.