A Capacity Enhanced AP-RIS Joint Optimization Scheme for Irregular Intelligent Surface-Assisted Cell-Free Massive MIMO Systems

Abstract

Due to its ability to avoid inter-cell interference, cell-free massive multiple-input multiple-output (MIMO) has become a potential enabling technology for 6G. Reconfigurable intelligence surface (RIS) can provide auxiliary pathways be-tween access points (APs) and users at a low cost, making it possible to increase system capacity. Integrating RIS into the cell-free MIMO system certainly has great advantages, but the channel estimation overhead arises for a great deal of RISs cannot be ignored. Then how to increase the system capacity with a reasonable number of RISs becomes a pressing issue. To tackle this problem, this paper proposes a novel AP and RIS joint optimization scheme for irregular RISs-assisted cell-free networks to enhance the system weighted sum rate (WSR). We formulate a WSR maximization problem with respect to the topology of RISs, the beamforming of APs, and the phase shifts of RISs. To cope with the above non-convex problem, an alternating optimization algorithm is proposed to decompose the non-convex problem into three convex sub-problems. Simulation results show that by using our proposed AP-RIS joint optimization scheme, the irregular RIS-assisted cell-free system can achieve higher system capacity than the conventional non- RIS-assisted cell-free system and regular RIS-assisted cell-free system.