Integrated Sensing and Communication Systems With Simultaneous Public and Confidential Transmission

Integrated sensing and communications (ISACs) technique is being considered as a promising technique for future networks. Facing the diverse services required for different nodes, in this article, we investigate the ISAC systems with simultaneous public and confidential transmission, where an ISAC base station simultaneously provides integrated public and confidential services for different nodes and performs target tracking using the echo of communication signals. We study the optimization of public, confidential signals, and artificial noise (AN) in both the time-invariant and time-varying channels. Our primary goal is to minimize the differences between the actual and desired beampatterns, while meeting the constraints of the public message rate (PMR) and confidential message secrecy rate (CMSR). For time-invariant channels with typically negligible estimation error of the channel state information (CSI), we aim to synthesize the target beampattern while satisfying the PMR and CMSR constraints. To this end, we first propose a successive convex approximation-based algorithm to jointly design the transmit covariance matrices and the AN covariance matrix; we then propose a low-complexity two-stage algorithm that is more suitable for the practical implementation. The proposed algorithms are further extended to the time-varying channels where the estimated may contain large errors. Simulation results are provided and verify the effectiveness of the proposed algorithms.