Sensing-Aided Secure Multicast in Two-Level Rotatable Antenna-Enabled ISAC Systems: Modeling and Optimization

2026-05-09

AI Summary

This work addresses the challenges in physical-layer secure multicasting, where fixed antenna arrays struggle to simultaneously serve multiple legitimate users and suppress eavesdropping, particularly when the eavesdropper’s channel state information is unknown. To overcome this, we propose a novel dual-level rotatable antenna architecture that integrates array-level and element-level rotation with analog beamforming, augmented by a sensing-assisted mechanism. Leveraging the Cramér-Rao bound, we characterize an angular uncertainty region for the eavesdropper and formulate a CRB-aware max-min secrecy rate optimization problem. The solution combines maximum likelihood estimation, Jensen’s inequality-based lower-bound reformulation, smooth approximation, and an alternating optimization algorithm based on manifold and projected gradients. Simulations demonstrate that the proposed scheme significantly outperforms baseline methods in both secrecy rate and robustness, while radiation patterns confirm that dual-level rotation effectively enables high-gain coverage for legitimate users and strong suppression in the eavesdropping region.

Abstract

In physical layer security, the channel state information (CSI) of passive eavesdroppers is usually difficult to obtain, which has motivated sensing-aided secure communication (SASC). However, in secure multicast scenarios, conventional fixed-position antennas (FPAs) provide limited spatial flexibility for simultaneously serving multiple legitimate users and suppressing leakage toward possible eavesdropper directions. Motivated by this, a novel two-level rotatable antenna (RA)-enabled sensing-aided secure multicast scheme is proposed in this paper. In the proposed architecture, array-level and element-wise rotations are jointly exploited with analog beamforming for user enhancement and leakage suppression. To characterize imperfect eavesdropper sensing, the maximum likelihood estimator and the corresponding Cramér-Rao bound (CRB) are derived to quantify the angular estimation accuracy. Based on the derived CRB, a probabilistic angular uncertainty region is constructed. A CRB-aware max-min secrecy-rate problem is then formulated by evaluating the eavesdropper leakage over sampled high-probability directions within this region. The non-convex problem is handled through a tractable lower-bound reformulation based on Jensen's inequality and smooth approximation, followed by an alternating optimization algorithm combining manifold optimization and projected-gradient updates. Simulation results show the effectiveness and robustness of the proposed scheme compared with various benchmarks. Beam patterns further reveal that array-level and element-wise rotations play complementary roles in maintaining strong gains toward legitimate users and forming a low-gain region over the eavesdropper angular uncertainty interval.

Problem

• secure multicast
• physical layer security
• eavesdropper CSI
• spatial flexibility
• information leakage

Innovation

• Rotatable Antenna
• Sensing-Aided Secure Communication
• Cramér-Rao Bound
• Secure Multicast
• Manifold Optimization