Passive Beamforming Design for Intelligent Reflecting Surface Assisted MIMO Systems

TL;DR

This paper proposes novel passive beamforming strategies for IRS-assisted MIMO systems, optimizing phase shifts and active beamforming to enhance system performance with practical discrete phase constraints.

Contribution

It introduces a tractable non-convex QCQP formulation for IRS passive beamforming and develops low-complexity iterative solutions with convergence guarantees.

Findings

Proposed solutions outperform benchmarks in simulations.

Effective handling of discrete phase shifts at IRS.

Convergence to locally optimal solutions.

Abstract

Intelligent reflecting surfaces (IRSs) constitute passive devices, which are capable of adjusting the phase shifts of their reflected signals, and hence they are suitable for passive beamforming. In this paper, we conceive their design with the active beamforming action of multiple-input multipleoutput (MIMO) systems used at the access points (APs) for improving the beamforming gain, where both the APs and users are equipped with multiple antennas. Firstly, we decouple the optimization problem and design the active beamforming for a given IRS configuration. Then we transform the optimization problem of the IRS-based passive beamforming design into a tractable non-convex quadratically constrained quadratic program (QCQP). For solving the transformed problem, we give an approximate solution based on the technique of widely used semidefinite relaxation (SDR). We also propose a low-complexity iterative solution. We further prove that it can converge to a locally optimal value. Finally, considering the practical scenario of discrete phase shifts at the IRS, we give the quantization design for IRS elements on basis of the two solutions. Our simulation results demonstrate the superiority of the proposed solutions over the relevant benchmarks.