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RIS-Aided Integrated Sensing and Communication Systems under Dual-polarized Channels

Dongnan Xia, Cunhua Pan, Hong Ren, Zhiyuan Yu, Yasheng Jin, Jiangzhou Wang

TL;DR

This work investigates a RIS-aided integrated sensing and communication (ISAC) system that uses dual-polarized (DP) channels at both the base station and the RIS. It develops a two-stage alternating optimization framework: a penalty-based method to optimally design the DP beamforming $\\mathbf{F}_k$ and a majorization-minimization (MM) approach to optimize the DP RIS phase shifts $\\boldsymbol{\\Phi}$, with a WMMSE reformulation guiding the joint design. The DP architecture, including cross-polarization components and XPD effects, yields notable gains in sum rate over traditional single-polarization setups, while preserving sensing performance via MVDR-based radar SNR constraints. The results demonstrate beneficial trade-offs between sensing quality and communication throughput, show the impact of RIS size and phase quantization, and reveal polarization-driven beampattern characteristics that enhance joint sensing and communication capabilities in 6G scenarios.

Abstract

This paper considers reconfigurable intelligent surface (RIS)-aided integrated sensing and communication (ISAC) systems under dual-polarized (DP) channels. Unlike the existing ISAC systems, which ignored polarization of electromagnetic waves, this study adopts DP base station (BS) and DP RIS to serve users with a pair of DP antennas. The achievable sum rate is maximized through jointly optimizing the beamforming matrix at the DP BS, and the reflecting coefficients at the DP RIS. To address this problem, we first utilize the weighted minimum mean-square error (WMMSE) method to transform the objective function into a more tractable form, and then an alternating optimization (AO) method is employed to decouple the original problem into two subproblems. Due to the constant modulus constraint, the DP RIS reflection matrix optimization problem is addressed by the majorization-minimization (MM) method. For the DP beamforming matrix, we propose a penalty-based algorithm that can obtain a low-complexity closed-form solution. Simulation results validate the advantage of deploying DP transmit array and DP RIS in the considered ISAC systems.

RIS-Aided Integrated Sensing and Communication Systems under Dual-polarized Channels

TL;DR

This work investigates a RIS-aided integrated sensing and communication (ISAC) system that uses dual-polarized (DP) channels at both the base station and the RIS. It develops a two-stage alternating optimization framework: a penalty-based method to optimally design the DP beamforming and a majorization-minimization (MM) approach to optimize the DP RIS phase shifts , with a WMMSE reformulation guiding the joint design. The DP architecture, including cross-polarization components and XPD effects, yields notable gains in sum rate over traditional single-polarization setups, while preserving sensing performance via MVDR-based radar SNR constraints. The results demonstrate beneficial trade-offs between sensing quality and communication throughput, show the impact of RIS size and phase quantization, and reveal polarization-driven beampattern characteristics that enhance joint sensing and communication capabilities in 6G scenarios.

Abstract

This paper considers reconfigurable intelligent surface (RIS)-aided integrated sensing and communication (ISAC) systems under dual-polarized (DP) channels. Unlike the existing ISAC systems, which ignored polarization of electromagnetic waves, this study adopts DP base station (BS) and DP RIS to serve users with a pair of DP antennas. The achievable sum rate is maximized through jointly optimizing the beamforming matrix at the DP BS, and the reflecting coefficients at the DP RIS. To address this problem, we first utilize the weighted minimum mean-square error (WMMSE) method to transform the objective function into a more tractable form, and then an alternating optimization (AO) method is employed to decouple the original problem into two subproblems. Due to the constant modulus constraint, the DP RIS reflection matrix optimization problem is addressed by the majorization-minimization (MM) method. For the DP beamforming matrix, we propose a penalty-based algorithm that can obtain a low-complexity closed-form solution. Simulation results validate the advantage of deploying DP transmit array and DP RIS in the considered ISAC systems.
Paper Structure (28 sections, 75 equations, 9 figures, 3 algorithms)

This paper contains 28 sections, 75 equations, 9 figures, 3 algorithms.

Table of Contents

  1. Introduction
  2. SYSTEM MODEL AND PROBLEM FORMULATION
  3. DP transmission signal
  4. DP channel model
  5. DP RIS
  6. PROBLEM FORMULATION
  7. Communication performance metric
  8. Sensing performance metric
  9. Optimization Model
  10. PROPOSED ALGORITHM
  11. Reformulation of the Original Problem
  12. Optimization of the DP Phase-Shift Matrix $\mathbf{\Phi}$
  13. Optimization of the DP precoding matrix $\mathbf{W}$
  14. Outer Layer Update
  15. Inner Layer Optimization
  16. ...and 13 more sections

Figures (9)

  • Figure 1: A DP RIS-aided ISAC system.
  • Figure 2: The simulation system scenario.
  • Figure 3: Convergence behavior of the proposed algorithm
  • Figure 4: Convergence behavior of the constraints in Algorithm \ref{['Alg-pdd']}
  • Figure 5: Comparison between SP and DP scenarios
  • ...and 4 more figures