Joint Beamforming and Resource Coordination for RIS-Aided ISAC Over Secure LAWNs

Integrated sensing and communication (ISAC) has emerged as a key enabler for next-generation wireless networks, providing a unified framework for spectrum-efficient data transmission and environmental sensing. This paper presents a joint beamforming strategy for a reconfigurable intelligent surface (RIS)-assisted ISAC system. We jointly optimize the active beamforming at the base station and the passive beamforming at the RIS to serve legitimate unmanned aerial vehicles (UAVs) while detecting potential unauthorized UAVs. The goal is to maximize the average sum-rate of all legitimate UAVs under constraints on radar sensing signal-to-noise ratio, the transmit power, and the reflection coefficients of the RIS. To address the non-convex optimization problem, we develop an efficient low-complexity solution based on fractional programming and alternating optimization. Simulation results show that the proposed algorithm significantly improves the data rate compared with benchmarks, validating the effectiveness of RIS in harmonizing communication and target sensing functionalities for low-altitude networks.