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

2025-05-30

AI Summary

This work addresses the joint optimization of legitimate unmanned aerial vehicle (UAV) communication rate maximization and illicit UAV sensing in a reconfigurable intelligent surface (RIS)-empowered integrated sensing and communication (ISAC) system for low-altitude secure networks. Under constraints on radar signal-to-noise ratio, base station transmit power, and RIS reflection coefficient modulus, we jointly optimize the active precoding at the dual-functional base station (DFBS) and passive beamforming at the RIS. To the best of our knowledge, this is the first study to achieve coordinated beam design between DFBS and RIS in low-altitude ISAC scenarios. We propose a low-complexity algorithm integrating fractional programming and alternating optimization, with guaranteed theoretical convergence. Simulation results demonstrate that, compared to decoupled optimization benchmarks, the proposed scheme significantly improves the aggregate communication rate of legitimate UAVs. Moreover, the RIS effectively enhances the synergy gain between communication and sensing functionalities, validating its critical role in simultaneously ensuring high communication performance and high-precision target sensing.

Technology Category

• Intelligent Robots: Learning & Optimization for ROB
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Security and Privacy: Security and privacy of machine learning and AI applications
• Search and Retrieval-Augmented AI: Vertical and domain-specific search

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.

Problem

• Balancing spectral efficiency and sensing accuracy in RIS-empowered ISAC systems
• Jointly optimizing active and passive beamforming for secure UAV communication
• Maximizing legitimate UAV sum-rate under sensing and power constraints

Innovation

• Coordinated beamforming for RIS-empowered ISAC systems
• Joint active and passive beamforming optimization
• Low-complexity fractional programming with alternating optimization