Hao Jiang, Zhaolin Wang, Yuanwei Liu, Arumugam Nallanathan, Zhiguo Ding
A sensing-aided covert communication network empowered by pinching antenna systems (PASS) is proposed in this work. Unlike conventional fixed-position multiple-input multiple-output (MIMO) arrays, PASS reconfigures wireless channels by repositioning pinching antennas (PAs) to enhance transmission covertness. To further obtain the adversary’s channel state information (CSI), a sensing function is leveraged to track the malicious warden’s movements. In particular, this paper first proposes an extended Kalman filter (EKF) based approach to fulfilling the tracking function. Building on this, a covert communication problem is formulated as a joint design of beamforming, artificial noise (AN) signals, and PA positions. Then, the beamforming and AN design subproblems are resolved using a subspace approach, while the PA position optimization subproblem is handled by a deep reinforcement learning (DRL) approach by treating the evolution of the warden’s mobility status as a temporally correlated process. Numerical results are presented and demonstrate that: i) the EKF approach can accurately track the warden’s CSI with low complexity, ii) the effectiveness of the proposed solution is verified by its outperformance over the greedy and searching-based benchmarks, and iii) with new design degrees of freedom (DoFs), the performance of PASS is superior to the conventional fully-digital MIMO systems.