Joint Beamforming Design for the STAR-RIS-Enabled ISAC Systems with Multiple Targets and Multiple Users

TL;DR

This work addresses joint sensing and communications in a STAR-RIS-enabled ISAC system with multiple targets and users by introducing signature sequence modulation to differentiate echoes from multiple targets. An alternating optimization framework jointly designs DFBS transmit beams and STAR-RIS coefficients to maximize the minimum sensing beam pattern gain under interference, QoS, and power constraints, by decomposing the problem into two SDP-friendly subproblems via SDR. The method iteratively solves for beamforming and STAR-RIS phases, with rank-one solutions recovered through standard randomization or decomposition, and converges to a local optimum. Simulation results show that the proposed SS-STAR-RIS scheme outperforms random-phase and conventional RIS baselines in terms of the minimum sensing gain, while highlighting the sensing-communication tradeoff as SINR requirements and RIS size change.

Abstract

In this paper, the sensing beam pattern gain under simultaneously transmitting and reflecting reconfigurable intelligent surfaces (STAR-RIS)-enabled integrated sensing and communications (ISAC) systems is investigated, in which multiple targets and multiple users exist. However, multiple targets detection introduces new challenges, since the STAR-RIS cannot directly send sensing beams and detect targets, the dual-functional base station (DFBS) is required to analyze the echoes of the targets. While the echoes reflected by different targets through STAR-RIS come from the same direction for the DFBS, making it impossible to distinguish them. To address the issue, we first introduce the signature sequence (SS) modulation scheme to the ISAC system, and thus, the DFBS can detect different targets by the SS-modulated sensing beams. Next, via the joint beamforming design of DFBS and STAR-RIS, we develop a maxmin sensing beam pattern gain problem, and meanwhile, considering the communication quality requirements, the interference limitations of other targets and users, the passive nature constraint of STAR-RIS, and the total transmit power limitation. Then, to tackle the complex non-convex problem, we propose an alternating optimization method to divide it into two quadratic semidefinite program subproblems and decouple the coupled variables. Drawing on mathematical transformation, semidefinite programming, as well as semidefinite relaxation techniques, these two subproblems are iteratively sloved until convergence, and the ultimate solutions are obtained. Finally, simulation results are conducted to validate the benefits and efficiency of our proposed scheme.

Figures (7)

• Figure 1: STAR-RIS-enabled ISAC system model.
• Figure 2: Simulation setup for STAR-RIS-enabled ISAC system.
• Figure 3: Beam pattern gain versus the number of iterations. (a) With various $\gamma$ and $N$. (b) With various $\eta$.
• Figure 4: The amplitude of each STAR-RIS element under different communication thresholds. (a) $\gamma=10$dB, $N=40$. (b) $\gamma=16$dB, $N=40$.
• Figure 5: Beam pattern gain versus the DFBS transmit power $P^{\text{max}}$.