Cell-Free MIMO Systems Powered by Intelligent Reflecting Surfaces

TL;DR

This paper introduces a novel two-step algorithm for cell-free MIMO systems with IRSs, leveraging statistical and short-term channel information to enhance performance while reducing complexity and overhead.

Contribution

It proposes a new long-term passive beamforming method using S-CSI and a joint short-term active precoding scheme, improving efficiency over existing approaches.

Findings

The proposed scheme outperforms benchmark methods in simulations.

Significant performance gains are achieved in cell-free MIMO with IRSs.

The approach reduces computational complexity and signaling overhead.

Abstract

Cell-free massive multiple-input multiple-output (MIMO) and intelligent reflecting surface (IRS) are considered as the prospective multiple antenna technologies for beyond the fifth-generation (5G) networks. Cell-free MIMO systems powered by IRSs, combining both technologies, can further improve the performance of cell-free MIMO systems at low cost and energy consumption. Prior works focused on instantaneous performance metrics and relied on alternating optimization algorithms, which impose huge computational complexity and signaling overhead. To address these challenges, we propose a novel two-step algorithm that provides the long-term passive beamformers at the IRSs using statistical channel state information (S-CSI) and short-term active precoders and long-term power allocation at the access points (APs) to maximize the minimum achievable rate. Simulation results verify that the proposed scheme outperforms benchmark schemes and brings a significant performance gain to the cell-free MIMO systems powered by IRSs.