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

TL;DR

The paper tackles downlink ISAC with dual semi-passive RISs, aiming to maximize the minimum user SINR under discrete RIS phase shifts. It introduces a sensing-assisted framework that uses 2D-MUSIC angle estimation from RIS echoes to tighten the discrete phase-shift search, enabling two low-complexity strategies: a GS algorithm for small RIS and a 1D per-element search for large RIS. An alternating optimization scheme couples SDR-based BS beamforming with sensing-guided RIS phase-shift design, achieving near-continuous performance and outperforming single-RIS and conventional discrete approaches. Numerical results confirm substantial gains in fairness and efficiency, demonstrating practical viability for multi-user RIS-assisted ISAC in dynamic environments.

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.

Figures (9)

• Figure 1: A dual-RIS-assisted ISAC system.
• Figure 2: The transmission cycle structure.
• Figure 3: The convergence of the GS algorithm under different $b$ values.
• Figure 4: Fairness varies with the number of BS antennas $N_t$ and the transmission power $P_{\rm max}$.
• Figure 5: Comparison of the max-min SINR of different algorithms.