Quantum Computing Based Optimization for Intelligent Reflecting Surface (IRS)-Aided Cell-Free Network

Abstract

Intelligent reflecting surface (IRS) enables the control of propagation characteristics and is attracting considerable attention as a technology to improve energy utilization efficiency in 6th generation mobile communication systems. As cell-free networks with multiple distributed base stations (BSs) can communicate in a coordinated manner, they are being actively researched as a new network architecture to resolve the problem of inter-cell interference in conventional cellular networks. The introduction of the IRS into the cell-free network can avoid shadowing at a lower cost with less power consumption. Thus, in this study, we considered the case of communication with user equipment (UE) in a shadowing environment using IRS in a cell-free network that contained distributed BSs with a single antenna. Moreover, the selection of multiple access methods was derived according to the numbers of BSs, IRSs, and UEs. In addition, we proposed a quadratic unconstrained binary optimization formulation to optimize the IRS reflection coefficient using quantum computing. The simulation results verified that the application of the proposed method resulted in a more efficient communication. Thus, this study clarifies that the optimum control method in every communication environment and aims to act as a stepping stone to optimize the entire cell-free system.