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Active RIS Aided ISAC Systems: Beamforming Design and Performance Analysis

Zhiyuan Yu, Hong Ren, Cunhua Pan, Gui Zhou, Boshi Wang, Mianxiong Dong, Jiangzhou Wang

TL;DR

The paper addresses joint radar-sensing and communications in an active RIS-aided ISAC system, formulating a nonconvex problem to maximize radar SINR while enforcing QoS and power constraints. It proposes an alternating optimization framework that combines majorization-minimization and semidefinite relaxation to iteratively optimize the DFRC-BS beamforming and the active RIS coefficients. Key contributions include deriving radar SINR scaling with the number of RIS elements, analyzing power allocation between the BS and RIS for moderate element counts, and proposing deployment strategies near the sensing target. Numerical results show substantial radar SINR gains for active RIS over passive RIS and reveal practical insights for power budgeting, RIS placement, and CSI robustness, highlighting the active RIS as a potent tool for RCC in 6G settings.

Abstract

This paper considers an active reconfigurable intelligent surface (RIS)-aided integrated sensing and communication (ISAC) system. We aim to maximize radar signal-to-interference-plus-noise-ratio (SINR) by jointly optimizing the beamforming matrix at the dual-function radar-communication (DFRC) base station (BS) and the reflecting coefficients at the active RIS subject to the quality of service (QoS) constraints of communication users (UE) and the transmit power constraints of active RIS and DFRC BS. To tackle the optimization problem, the majorization-minimization (MM) algorithm is applied to address the nonconvex radar SINR objective function, and the resulting quartic problem is solved by developing an semidefinite relaxation (SDR)-based approach. Moreover, we derive the scaling order of the radar SINR with a large number of reflecting elements. Next, the transmit power allocation problem and the deployment strategy of the active RIS are studied with a moderate number of reflecting elements. Finally, we validate the potential of the active RIS in ISAC systems compared to passive RIS. Additionally, we deliberate on several open problems that remain for future research.

Active RIS Aided ISAC Systems: Beamforming Design and Performance Analysis

TL;DR

The paper addresses joint radar-sensing and communications in an active RIS-aided ISAC system, formulating a nonconvex problem to maximize radar SINR while enforcing QoS and power constraints. It proposes an alternating optimization framework that combines majorization-minimization and semidefinite relaxation to iteratively optimize the DFRC-BS beamforming and the active RIS coefficients. Key contributions include deriving radar SINR scaling with the number of RIS elements, analyzing power allocation between the BS and RIS for moderate element counts, and proposing deployment strategies near the sensing target. Numerical results show substantial radar SINR gains for active RIS over passive RIS and reveal practical insights for power budgeting, RIS placement, and CSI robustness, highlighting the active RIS as a potent tool for RCC in 6G settings.

Abstract

This paper considers an active reconfigurable intelligent surface (RIS)-aided integrated sensing and communication (ISAC) system. We aim to maximize radar signal-to-interference-plus-noise-ratio (SINR) by jointly optimizing the beamforming matrix at the dual-function radar-communication (DFRC) base station (BS) and the reflecting coefficients at the active RIS subject to the quality of service (QoS) constraints of communication users (UE) and the transmit power constraints of active RIS and DFRC BS. To tackle the optimization problem, the majorization-minimization (MM) algorithm is applied to address the nonconvex radar SINR objective function, and the resulting quartic problem is solved by developing an semidefinite relaxation (SDR)-based approach. Moreover, we derive the scaling order of the radar SINR with a large number of reflecting elements. Next, the transmit power allocation problem and the deployment strategy of the active RIS are studied with a moderate number of reflecting elements. Finally, we validate the potential of the active RIS in ISAC systems compared to passive RIS. Additionally, we deliberate on several open problems that remain for future research.
Paper Structure (37 sections, 78 equations, 11 figures, 1 algorithm)

This paper contains 37 sections, 78 equations, 11 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. Transmission Signal
  4. Channel Model
  5. Active RIS Model
  6. Problem Formulation
  7. Radar Performance Metric
  8. Communication Performance Metric
  9. Optimization Problem
  10. Proposed Solver via MM algorithm
  11. Reformulation of the Objective Function
  12. Optimize $\mathbf{W}$
  13. Optimize $\mathbf{\Phi}$
  14. Radar SINR Metric
  15. Active RIS Transmit Power Constraint
  16. ...and 22 more sections

Figures (11)

  • Figure 1: An active RIS-aided ISAC system.
  • Figure 2: The simulation system setup.
  • Figure 3: Convergence behaviors.
  • Figure 4: Approximate radar SINR versus the the number of RIS elements $N$.
  • Figure 5: Radar SINR versus the number of RIS elements $N$.
  • ...and 6 more figures