This letter investigates the use of pilot-based codebook artificial noise (PCAN) in Integrated Sensing and Communication (ISAC) systems to enhance physical layer security. ISAC technology integrates communication and ...
详细信息
This letter investigates the use of pilot-based codebook artificial noise (PCAN) in Integrated Sensing and Communication (ISAC) systems to enhance physical layer security. ISAC technology integrates communication and sensing through shared resources, emphasizing the need for secure strategies. PCAN allows the receiver to extract information from the pilotcodebook, effectively removing interference and increasing secrecy capacity. The non-convex secrecy capacity optimization problem is addressed by decomposing it into simpler subproblems. A semidefinite relaxation (SDR) and alternating optimization algorithm is proposed to maximize secrecy capacity while maintaining sensing accuracy. Simulation results show significant improvements, particularly at low and moderate Signal-to-noise Ratio (SNR), with consistent gains at high SNRs. This work underscores the role of optimization techniques in enhancing secure communication and balancing secrecy with sensing performance in ISAC systems.
pilot-based codebook artificial noise (PCAN), which plays a crucial role in ensuring secure communication, is an emerging physical layer security technique. PCAN faces a significant challenge due to the unknown eavesd...
详细信息
pilot-based codebook artificial noise (PCAN), which plays a crucial role in ensuring secure communication, is an emerging physical layer security technique. PCAN faces a significant challenge due to the unknown eavesdropper channel. To address this issue, this letter re-models the eavesdropper channel using random matrix theory. By applying the eta -transform and Shannon-transform, the asymptotic expression for the eavesdropper channel capacity is derived under the condition of an unknown eavesdropper channel. The simulation result shows that when the number of transmitter antennas equals the number of eavesdropper antennas and the system dimension is large, the model can effectively characterize the eavesdropper channel capacity. Within this framework, the secrecy capacity is optimized using the Difference of Convex functions - Successive Convex Approximation (DC-SCA) algorithm, providing a new approach to improve the performance of PCAN.
暂无评论