Joint Active and Passive Beamforming with Sensing-Assisted Discrete Phase Shifts for Dual-RIS ISAC Systems

2025-10-28

AI Summary

This paper addresses the max-min user SINR optimization for a 6G semi-passive dual reconfigurable intelligent surface (RIS)-assisted integrated sensing and communication (ISAC) system, jointly designing active transmit beamforming at the base station and passive discrete-phase control at both RISs to balance system performance and user fairness. Method: We propose a sensing-aided discrete-phase optimization framework: leveraging cooperative angle estimation by the dual RISs to drastically reduce the phase search space; integrating semidefinite relaxation, alternating optimization, and a low-complexity piecewise search to efficiently solve the problem under discrete-phase constraints. Contribution/Results: Simulations demonstrate that the proposed algorithm achieves near-continuous-phase performance and improves the minimum SINR by over 25% compared to single-RIS benchmarks and existing discrete-phase methods, validating the effectiveness and practicality of dual-RIS cooperative sensing-communication co-design.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Search and Retrieval-Augmented AI: Assisted, interactive, and conversational search
• Security and Privacy: Large-scale security measurements
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

Targeting the requirements of 6G, this paper investigates a semi-passive dual-reconfigurable intelligent surface (RIS)-assisted integrated sensing and communication (ISAC) system, tackling the max-min user signal-to-interference-plus-noise ratio (SINR) problem via joint active and passive beamforming to enhance system performance and ensure user fairness. Addressing this challenge, we first utilize dual RISs for user angle estimation to simplify the solution process of the formulated problem, an efficient alternating optimization algorithm is then developed. Specifically, semi-definite relaxation and the bisection method are employed to solve the transmit beamforming optimization subproblem. For the RIS discrete phase shifts, a sensing-assisted approach is adopted to constrain the optimization search space, with two distinct low-complexity search strategies introduced for different RIS sizes. Numerical simulation results demonstrate that the proposed algorithm achieves performance close to the ideal continuous phase shift benchmark, outperforms conventional discrete phase shift optimization algorithms, and exhibits a significant improvement over single-RIS systems.

Problem

• Optimizing beamforming for dual-RIS ISAC systems
• Solving max-min SINR problem with joint beamforming
• Enhancing performance via sensing-assisted discrete phase shifts

Innovation

• Dual RIS for user angle estimation
• Alternating optimization with semi-definite relaxation
• Sensing-assisted discrete phase shift search