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Intelligent Reflecting Surface Aided Wireless Communication Systems: Joint Location and Passive Beamforming Design

Jintao Luo, Sixing Yin

TL;DR

This paper addresses the non-convex problem of maximizing the minimum user rate in an IRS-aided downlink MISO system by jointly optimizing BS beamforming, IRS phase shifts, and IRS location under a BS power constraint. It introduces an alternating optimization framework that decouples the problem into a beamforming/phase-shift subproblem and a location subproblem, solving them with convex surrogates and successive convex approximation, respectively. Numerical results show convergence and significant performance gains over benchmarks, including no-IRS and discrete-phase IRS schemes, with deployment height impacting the gains. The approach highlights the practical potential of strategically deploying IRSs and jointly designing their reflection properties to enhance fairness and spectral efficiency in multi-user wireless networks.

Abstract

Intelligent reflecting surface (IRS) has been widely studied in recent years, it has emerged as a new technology which can reflect the incident signal by intelligently configuring the reflection elements, thus changing the signal propagation environment, enhancing the signals users desire and suppressing the interference between users. In this paper, we study an IRS aided multi-users wireless communication where the base station (BS) sends a variety of signals, each user receives desired signals. In order to guarantee the fairness of wireless communications, we need to maximize the minimum rates of users, subject to the power constraint of BS and the phase constraint of IRS. Prior works on IRS mainly consider optimizing BS beamforming and IRS passive beamforming, this paper also aims to optimize the IRS location. The considered problem is shown to be non-convex, we decompose the problem into two subproblems, transforming the two subproblems into a lower bound problem and using alternating optimization (AO) and successive convex approximation (SCA) to solve them, respectively. Finally, the two subproblems are optimized alternately to make the objective function value converge in an acceptable range. Simulation results verify the convergence results of our proposed algorithm, and the performance improvement compared with the benchmark scheme in wireless communication system.

Intelligent Reflecting Surface Aided Wireless Communication Systems: Joint Location and Passive Beamforming Design

TL;DR

This paper addresses the non-convex problem of maximizing the minimum user rate in an IRS-aided downlink MISO system by jointly optimizing BS beamforming, IRS phase shifts, and IRS location under a BS power constraint. It introduces an alternating optimization framework that decouples the problem into a beamforming/phase-shift subproblem and a location subproblem, solving them with convex surrogates and successive convex approximation, respectively. Numerical results show convergence and significant performance gains over benchmarks, including no-IRS and discrete-phase IRS schemes, with deployment height impacting the gains. The approach highlights the practical potential of strategically deploying IRSs and jointly designing their reflection properties to enhance fairness and spectral efficiency in multi-user wireless networks.

Abstract

Intelligent reflecting surface (IRS) has been widely studied in recent years, it has emerged as a new technology which can reflect the incident signal by intelligently configuring the reflection elements, thus changing the signal propagation environment, enhancing the signals users desire and suppressing the interference between users. In this paper, we study an IRS aided multi-users wireless communication where the base station (BS) sends a variety of signals, each user receives desired signals. In order to guarantee the fairness of wireless communications, we need to maximize the minimum rates of users, subject to the power constraint of BS and the phase constraint of IRS. Prior works on IRS mainly consider optimizing BS beamforming and IRS passive beamforming, this paper also aims to optimize the IRS location. The considered problem is shown to be non-convex, we decompose the problem into two subproblems, transforming the two subproblems into a lower bound problem and using alternating optimization (AO) and successive convex approximation (SCA) to solve them, respectively. Finally, the two subproblems are optimized alternately to make the objective function value converge in an acceptable range. Simulation results verify the convergence results of our proposed algorithm, and the performance improvement compared with the benchmark scheme in wireless communication system.
Paper Structure (16 sections, 82 equations, 10 figures, 3 algorithms)

This paper contains 16 sections, 82 equations, 10 figures, 3 algorithms.

Table of Contents

  1. Introduction
  2. SYSTEM MODEL AND PROBLEM FORMULATION
  3. System Model
  4. Problem Formulation
  5. PROPOSED ALGORITHM
  6. Optimizing the Transmit Beamforming and Reflection Coefficient with given q
  7. IRS Location optimization
  8. Overall Algorithm
  9. NUMERICAL RESULTS
  10. Simulation Setup
  11. Baseline Schemes
  12. Convergence of the Proposed Algorithms
  13. IRS Performance Comparison
  14. CONCLUSION
  15. THE PROOF OF LEMMA2
  16. ...and 1 more sections

Figures (10)

  • Figure 1: An IRS-assisted multi-users communication system.
  • Figure 2: Simulation setup
  • Figure 3: The convergence behaviour of different height
  • Figure 4: IRS-assisted vs without IRS
  • Figure 5: Proposed Algorithm vs PSO
  • ...and 5 more figures