Achievable Rate Maximization for Aerial Intelligent Reflecting Surface-aided Cell-free Massive MIMO System

Abstract

An intelligent reflecting surface (IRS) has significant advantages in enhancing network coverage, spectrum efficiency, energy efficiency, and deployment costs. IRSs are envisioned to be a key technology in sixth-generation (6G) communication systems. Consisting of a new multiple-input-multiple-output (MI-MO) network architecture, cell-free massive MIMO is capable of providing users with high quality-of-service (QoS) and is consequently expected to be the core architecture of the next generation communication system. This paper first considers an aerial intelligent reflecting surface (AIRS)-aided cell-free downlink system, where multiple access points (APs) equipped with single or multiple antennas serve a smaller number of users by using an AIRS to assist communication. Both the APs and the AIRS are controlled by a central processing unit (CPU). The goal of this paper is to maximize the achievable user transmission rate. We use an iterative optimization strategy to jointly design the power allocation at each AP, the phase shift matrix of the AIRS, and the beamforming vector at each AP to obtain the optimal solution. The simulation results show that we can obtain a good achievable rate performance using the proposed optimization strategy.