Tracking-Assisted Robust Secure Transmission Against a Mobile Eavesdropper in Cell-Free ISAC Networks

In this paper, we propose a tracking-assisted robust secure transmission framework for cell-free integrated sensing and communication (ISAC) networks that exploits distributed multistatic sensing to recursively track a mobile eavesdropper and quantify the associated position uncertainty. Since robust beamforming requires communication channel uncertainty rather than position uncertainty, directly incorporating tracking information into secure transmission is nontrivial. This challenge becomes more pronounced in cell-free ISAC, where the common position uncertainty propagates differently to the channels of geographically distributed access points (APs), resulting in coupled AP-specific channel uncertainties. To address this challenge, we fuse multistatic sensing measurements from distributed APs and sensing receivers using an extended Kalman filter (EKF) and propose a Jacobian-based anisotropic ellipsoidal uncertainty model that maps the EKF position-error covariance to coupled AP-specific channel uncertainties. Based on the proposed model, we formulate a robust sum secrecy-rate maximization problem under per-AP transmit-power and sensing mean-square error constraints and develop an efficient alternating optimization algorithm for the joint design of communication beamforming and sensing signals. Simulation results demonstrate a fundamental trade-off between tracking accuracy and secrecy performance, the benefits of distributed multistatic sensing and cooperative transmission in cell-free ISAC, and the effectiveness of the proposed robust design in improving secrecy reliability under mobility-induced channel uncertainty.

Robust Beamforming and Time Allocation for Time-Division Cell-Free Near-Field ISAC

In this paper, we propose a time-division near-field integrated sensing and communication (ISAC) framework for cell-free multiple-input multiple-output (MIMO), where sensing and downlink communication are separated in time. During the sensing phase, user locations are estimated and used to construct location-aware channels, which are then exploited in the subsequent communication phase. By explicitly modeling the coupling between sensing-induced localization errors and channel-estimation errors, we capture the tradeoff between sensing accuracy and communication throughput. Based on this model, we jointly optimize the time-allocation ratio, sensing covariance matrix, and robust downlink beamforming under imperfect channel state information (CSI). The resulting non-convex problem is addressed via a semidefinite programming (SDP)-based reformulation within an alternating-optimization framework. To further reduce computational complexity, we also propose two low-complexity suboptimal designs: an error-ignorant scheme and a maximum ratio transmission (MRT)-based scheme. Simulation results show that the proposed scheme significantly improves localization accuracy over far-field and monostatic setups, thereby reducing channel estimation errors and ultimately enhancing the achievable rate. Moreover, the error-ignorant scheme performs well under stringent sensing requirements, whereas the MRT-based scheme remains robust over a wide range of sensing requirements by adapting the time-allocation ratio, albeit with some beamforming loss.

Secrecy Enhancement for UAV-enabled Integrated Sensing and Communication System

In this correspondence, we propose an unmanned aerial vehicle (UAV)-enabled integrated sensing and communication (ISAC) system, where a full-duplex UAV equipped with uniform planar array (UPA) is adopted as a base station for the multiuser downlink communications, while sensing and jamming a passive ground eavesdropper. The goal of this work is to maximize the sum secrecy rate of ground users subject to the constraints of sensing accuracy and UAV's operational capability by jointly optimizing the transceiver beamforming and UAV's trajectory. To this end, we develop the algorithmic solution based on block coordinate descent (BCD) and semidefinite programming (SDP) relaxation techniques, whose performance is verified via simulations indicating its efficacy in improving communication security with the sufficient mission period.