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Joint Mode Selection and Beamforming Designs for Hybrid-RIS Assisted ISAC Systems

Yingbin Lin, Feng Wang, Xiao Zhang, Guojun Han, Vincent K. N. Lau

TL;DR

This work tackles joint mode selection and beamforming in a hybrid-RIS assisted ISAC system, aiming to maximize the minimum sensing beampattern gain among $L$ targets while satisfying CU SINR constraints. It introduces an alternating-optimization framework that uses semidefinite relaxation (SDR) to obtain the BS beamformers (with rank-one reconstruction) and a SDR+SCA strategy to jointly determine RIS mode selection and reflection coefficients. The approach decomposes the MINLP into two convex subproblems solved iteratively, with convergence to a local optimum and quantified complexity. Numerical results demonstrate substantial performance gains over baselines and highlight the importance of tunable active RIS elements in enhancing ISAC performance under practical power and QoS constraints.

Abstract

This paper considers a hybrid reconfigurable intelligent surface (RIS) assisted integrated sensing and communication (ISAC) system, where each RIS element can flexibly switch between the active and passive modes. Subject to the signal-to-interference-plus-noise ratio (SINR) constraint for each communication user (CU) and the transmit power constraints for both the base station (BS) and the active RIS elements, with the objective of maximizing the minimum beampattern gain among multiple targets, we jointly optimize the BS transmit beamforming for ISAC and the mode selection of each RIS reflecting element, as well as the RIS reflection coefficient matrix. Such formulated joint hybrid-RIS assisted ISAC design problem is a mixed-integer nonlinear program, which is decomposed into two low-dimensional subproblems being solved in an alternating manner. Specifically, by using the semidefinite relaxation (SDR) technique along with the rank-one beamforming construction process, we efficiently obtain the optimal ISAC transmit beamforming design at the BS. Via the SDR and successive convex approximation (SCA) techniques, we jointly determine the active/passive mode selection and reflection coefficient for each RIS element. Numerical results demonstrate that the proposed design solution is significantly superior to the existing baseline solutions.

Joint Mode Selection and Beamforming Designs for Hybrid-RIS Assisted ISAC Systems

TL;DR

This work tackles joint mode selection and beamforming in a hybrid-RIS assisted ISAC system, aiming to maximize the minimum sensing beampattern gain among targets while satisfying CU SINR constraints. It introduces an alternating-optimization framework that uses semidefinite relaxation (SDR) to obtain the BS beamformers (with rank-one reconstruction) and a SDR+SCA strategy to jointly determine RIS mode selection and reflection coefficients. The approach decomposes the MINLP into two convex subproblems solved iteratively, with convergence to a local optimum and quantified complexity. Numerical results demonstrate substantial performance gains over baselines and highlight the importance of tunable active RIS elements in enhancing ISAC performance under practical power and QoS constraints.

Abstract

This paper considers a hybrid reconfigurable intelligent surface (RIS) assisted integrated sensing and communication (ISAC) system, where each RIS element can flexibly switch between the active and passive modes. Subject to the signal-to-interference-plus-noise ratio (SINR) constraint for each communication user (CU) and the transmit power constraints for both the base station (BS) and the active RIS elements, with the objective of maximizing the minimum beampattern gain among multiple targets, we jointly optimize the BS transmit beamforming for ISAC and the mode selection of each RIS reflecting element, as well as the RIS reflection coefficient matrix. Such formulated joint hybrid-RIS assisted ISAC design problem is a mixed-integer nonlinear program, which is decomposed into two low-dimensional subproblems being solved in an alternating manner. Specifically, by using the semidefinite relaxation (SDR) technique along with the rank-one beamforming construction process, we efficiently obtain the optimal ISAC transmit beamforming design at the BS. Via the SDR and successive convex approximation (SCA) techniques, we jointly determine the active/passive mode selection and reflection coefficient for each RIS element. Numerical results demonstrate that the proposed design solution is significantly superior to the existing baseline solutions.

Paper Structure

This paper contains 10 sections, 16 equations, 4 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model and Problem Formulation
  3. System Model
  4. Problem Formulation
  5. Proposed Design Solution
  6. Optimization of $(\left\{\boldsymbol{w}_{k}\right\}_{k=1}^{K},\boldsymbol{R}_{0})$ Under Given $(\{q_n\}_{n\in{\cal N}},\boldsymbol{\Phi})$
  7. Optimization of $(\{q_n\}_{n\in{\cal N}},\boldsymbol{\Phi})$ Under Given $(\left\{\boldsymbol{w}_{k}\right\}_{k=1}^{K},\boldsymbol{R}_{0})$
  8. Proposed Algorithm and Analysis
  9. Numerical Results
  10. Conclusion

Figures (4)

  • Figure 1: The hybrid active-passive RIS assisted ISAC system model, consisting of a number of $L$ targets and a number of $K$ CUs.
  • Figure 2: (a) The minimum target sensing beampattern gain; (b) the running time of proposed algorithm
  • Figure 3: The achieved minimum sensing beampattern gain for target sensing: (a) versus the RIS element number $N$; (b) versus the RIS transmission power budget $P^{\rm{ris}}_{\rm{max}}$; (c) versus CUs' SINR threshold $\Gamma$.
  • Figure 4: Performance evaluation with $L=2$ targets and $K=2$. (a) The normalized 3-D sensing beampattern gain profile. (b) The number ratio of active-to-passive RIS elements.