Physical Layer Security Optimization With Cramér-Rao Bound Metric in ISAC Systems Under Sensing-Specific Imperfect CSI Model

The integrated sensing and communication (ISAC) endows the next generation of wireless networks with the new paradigm to the security communication. In this paper, the dual-functional radar-communication (DFRC) with the property of spectral and energy efficiency is considered to strengthen the physical layer security (PLS) under the channel state information (CSI) uncertainty of the eavesdropper, where satisfies the tolerate sensing requirement and the minimum secrecy rate for each legitimate user. Specifically, we propose the PLS optimization model which employs the Cramér-Rao bound (CRB) as the sensing metric, and characterize the sensing-communication trade-off under the PLS enhancement. The efficiency closed-form solution composed of the generalized eigenvector and the power budge is derived for the case of single legitimate user with the perfect CSI of the eavesdropper. Considering the general case of multiple users, we first propose the novel sensing-specific imperfect CSI model to construct the inherent integration between the sensing capacity and the norm bound of the imperfect CSI. Further, the infinite uncertainty is handled by the S-procedure, and we propose the block coordinate descent (BCD) iterative algorithm to solve the PLS optimization problem comprising with the semidefinite relaxation (SDR) and the successive convex approximation (SCA) to address the non-convexity. Simulation results demonstrate the performance gain and the effectiveness of the proposed algorithm in the average secrecy rate over other baseline schemes.