Towards Reliable Communications in Intelligent Reflecting Surface-Aided Cell-Free MIMO Systems

Intelligent reflecting surface (IRS) and cell-free multiple-input multiple-output (CF-MIMO) systems are two promising multi-antenna technologies for the fifth generation and beyond (B5G) wireless communication systems. In this paper, we formulate a joint phase shift control and beamforming opti-mization problem to maximize the aggregate throughput subject to the reliability constraint of the users in an IRS-aided CF-MIMO system. We propose an alternating optimization (AO)-based algorithm, in which the joint problem is decomposed into a phase shift control subproblem and a beamforming subproblem. For the phase shift control subproblem, we propose a complex gradient descent (CGD)-based algorithm, which tackles the unit-modulus constraint and guarantees the aggregate throughput to be monotonic increasing in each iteration. We then propose a difference of convex programming (DCP)-based algorithm for beamforming optimization. Simulation results show that the proposed AO-based algorithm achieves an aggregate throughput that is 53.8% and 25.1% higher than the cellular MIMO system with zero-forcing beamformer and the IRS-aided CF-MIMO system with random phase shift control, respectively. Moreover, the reliability requirements of the users are satisfied with the proposed AO-based algorithm. Our results also demonstrate that the proposed algorithm improves the minimum throughput of the users and reduces the standard deviation of the throughput distribution.