Coordinated Beamforming for RIS-Empowered ISAC Systems over Secure Low-Altitude Networks

TL;DR

This paper introduces a joint beamforming optimization framework for RIS-empowered ISAC systems, enhancing communication for legitimate UAVs and sensing unauthorized UAVs in low-altitude networks.

Contribution

It proposes a novel low-complexity algorithm that jointly optimizes active and passive beamforming in RIS-empowered ISAC systems with convergence guarantees.

Findings

Achieves higher data rates compared to disjoint optimization methods.

Demonstrates RIS's effectiveness in balancing communication and sensing.

Provides a practical algorithm with convergence guarantees.

Abstract

Emerging as a cornerstone for next-generation wireless networks, integrated sensing and communication (ISAC) systems demand innovative solutions to balance spectral efficiency and sensing accuracy. In this paper, we propose a coordinated beamforming framework for a reconfigurable intelligent surface (RIS)-empowered ISAC system, where the active precoding at the dual-functional base station (DFBS) and the passive beamforming at the RIS are jointly optimized to provide communication services for legitimate unmanned aerial vehicles (UAVs) while sensing the unauthorized UAVs. The sum-rate of all legitimate UAVs are maximized, while satisfying the radar sensing signal-to-noise ratio requirements, the transmit power constraints, and the reflection coefficients of the RIS. To address the inherent non-convexity from coupled variables, we propose a low-complexity algorithm integrating fractional programming with alternating optimization, featuring convergence guarantees. Numerical results demonstrate that the proposed algorithm achieves higher data rate compared to disjoint optimization benchmarks. This underscores RIS's pivotal role in harmonizing communication and target sensing functionalities for low-altitude networks.