IRS-aided cell-free MIMO systems

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. IRS-aided cell-free MIMO systems, combining both technologies, can further improve the performance of cell-free MIMO systems at low cost and energy consumption. Prior works on IRS-aided cell-free MIMO systems focused on instantaneous performance metrics and relied on alternating optimization algorithms, which impose huge signal processing complexity and fronthaul signaling overhead. To address these challenges for cell-free MIMO with multiple IRSs, we propose a novel non-iterative two-step algorithm that provides the long-term passive beamformers at the IRSs and short-term active precoders and long-term power allocation at the access points (APs) to maximize the minimum average rate. Specifically, the long-term passive beamformers are derived based on statistical channel state information (S-CSI) to reduce the computational complexity and signaling overhead. Simulation results verify that the proposed scheme outperforms benchmark schemes and brings a significant performance gain to the IRS-aided cell-free MIMO systems.