A Novel SCA-Based Method for Beamforming Optimization in IRS/RIS-Assisted MU-MISO Downlink

TL;DR

This paper introduces a new successive convex approximation method for optimizing beamforming and phase-shifts in IRS-assisted MU-MISO downlink systems, achieving better performance and lower complexity than existing solutions.

Contribution

A novel SCA-based second-order cone programming approach that jointly optimizes transmit beamformers and IRS phase-shifts with improved efficiency.

Findings

Achieves superior performance over benchmark schemes.

Reduces computational complexity from O(Ns^7) to O(Ns^3.5).

Effectively minimizes transmit power under QoS constraints.

Abstract

In this letter, we consider the fundamental problem of jointly designing the transmit beamformers and the phase-shifts of the intelligent reflecting surface (IRS) / reconfigurable intelligent surface (RIS) to minimize the transmit power, subject to quality-of-service constraints at individual users in an IRS-assisted multiuser multiple-input single-output downlink communication system. In particular, we propose a new successive convex approximation based second-order cone programming approach in which all the optimization variables are simultaneously updated in each iteration. Our proposed scheme achieves superior performance compared to state-of-the-art benchmark solutions. In addition, the complexity of the proposed scheme is $O(N_{\mathrm s}^{3.5})$, while that of state-of-the-art benchmark schemes is $O(N_{\mathrm s}^{7})$, where $N_{\mathrm s}$ denotes the number of reflecting elements at the IRS.