Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming

TL;DR

This paper investigates how to jointly optimize active and passive beamforming in an IRS-assisted multiuser MISO wireless system to minimize transmit power while satisfying SINR constraints.

Contribution

It proposes a joint optimization framework for active and passive beamforming in IRS-enhanced wireless networks, addressing the non-convex problem.

Findings

Joint beamforming reduces transmit power effectively.

Proposed algorithms handle non-convex optimization challenges.

Enhanced spectral and energy efficiency demonstrated.

Abstract

Intelligent reflecting surface (IRS) is envisioned to be a new and revolutionizing technology for achieving spectrum and energy efficient wireless communication networks cost-effectively in the future. Specifically, an IRS consists of a large number of low-cost passive elements each reflecting the incident signal with a certain phase shift to collaboratively achieve beamforming and/or interference suppression at designated receivers. In this paper, we study an IRS-aided multiuser multiple-input single-output (MISO) wireless system where one IRS is deployed to assist in the communication from a multi-antenna access point (AP) to multiple single-antenna users. As such, each user receives the superposed signals from the AP as well as the IRS via its reflection. We aim to minimize the total transmit power at the AP by jointly optimizing the transmit beamforming by active antenna array at the AP and reflect beamforming by passive phase shifters at the IRS, subject to users' individual signal-to-interference-plus-noise ratio (SINR) constraints. However, the formulated problem is non-convex and difficult to be solved optimally.