A Two-Stage AP Selection Approach for Scalable User-Centric Cell-Free Massive MIMO Systems

People propose a novel two-phase access point (AP) selection method to improve the performance of user-centric cell-free massive MIMO systems. The first intermediate AP cluster stage connects users to nearby APs based on large-scale fading to optimize connection quality. The second final AP cluster stage allows users to connect to additional APs to boost spectral efficiency. The proposed approach considers channel state information, received signal strength, traffic load balancing, and scalability. The methodology involves uplink/downlink training and a multi-step decision process to form optimum AP clusters per user. Simulations in MATLAB demonstrate significant gains in spectral efficiency, energy efficiency, and complexity compared to existing techniques. The two-phase AP selection provides a practical solution to unlock the potential of cell-free massive MIMO for next-generation networks like indoor industrial implementations. This paper presents a comprehensive, scalable framework for AP selection that enhances key performance metrics in user-centric cell-free massive MIMO systems.