Secure Enhancement for RIS-Aided UAV with ISAC: Robust Design and Resource Allocation

This paper analyses the security performance of a reconfigurable intelligent surface (RIS)-aided unmanned aerial vehicle (UAV) communication system with integrated sensing and communications (ISAC). We consider a multiple-antenna UAV transmitting ISAC waveforms to simultaneously detect an untrusted target in the surrounding environment and communicate with a ground Internet-of-Things (IoT) device in the presence of an eavesdropper (Eve). Given that the Eve can conceal their channel state information (CSI) in practical scenarios, we assume that the CSI of the eavesdropper channel is imperfect. For this RIS-aided ISAC-UAV system, we aim to maximize the average communication secrecy rate by jointly optimizing UAV trajectory, RIS passive beamforming, transmit beamforming, and receive beamforming. However, this joint optimization problem is non-convex due to multi-variable coupling. As such, we solve the optimization using an efficient and tractable algorithm using a block coordinate descent (BCD) method. Specifically, we develop a successive convex approximation (SCA) algorithm based on semidefinite relaxation (SDR) to optimise the joint optimization as four separate non-convex subproblems. Numerical results show that our proposed algorithm can successfully ensure the accuracy of sensing targets and significantly improve the communication secrecy rate of the IoT communication devices.

Movable Antenna Enabled ISAC Beamforming Design for Low-Altitude Airborne Vehicles

In mobile systems with low-altitude vehicles, integrated sensing and communication (ISAC) is considered an effective approach to increase the transmission rate due to limited spectrum resources. To further improve the ISAC performance, this paper proposes a novel method called integrated sensing and communication-movable antenna (ISAC-MA) to optimize the antenna's position. Our goal is to support low-space vehicles by optimizing radar and communication joint beamforming and antenna position in the presence of clutter. This scheme not only guarantees the required signal-to-noise ratio (SNR) for sensing but also further improves the SNR for communication. A successive convex approximation (SCA)-based block coordinate descent (BCD) algorithm is proposed to maximize communication capacity under the condition of sensing SNR. Numerical results show that, compared with the traditional ISAC system and various benchmark schemes, the proposed ISAC-MA system can achieve higher communication capacity under the same sensing SNR constraints.

Improving Physical-Layer Security in ISAC-UAV System: Beamforming and Trajectory Optimization

This paper investigates a novel unmanned aerial vehicle (UAV) secure communication system with integrated sensing and communications. We consider wireless security enhancement for a multiple-antenna UAV transmitting ISAC waveforms to communicate with multiple ground Internet-of-Thing devices and detect the surrounding environment. Specifically, we aim to maximize the average communication secrecy rate by optimizing the UAV trajectory and beamforming vectors. Given that the UAV trajectory optimization problem is non-convex due to multi-variable coupling develop an efficient algorithm based on the successive convex approximation (SCA) algorithm. Numerical results show that our proposed algorithm can ensure the accuracy of sensing targets and improve the communication secrecy rate.