A Study on the Access Point Clustering algorithm in Cell-Free massive MIMO System with Finite Fronthaul Capacity for Multimedia Communication

Cell-Free massive multiple-input multiple-output (MIMO) is gaining significant attention as a key area of interest in the beyond fifth-generation (B5G) and six-generation (6G) due to its ability to achieve better performance than traditional cellular systems. Cell-Free massive MIMO involves access points (APs) within a coverage area being connected to a single central processing unit (CPU) via fronthaul links, and these APs cooperated to support users. However, this system demands a significant amount of fronthaul capacity. To satisfy the finite fronthaul capacity, a system is configured using low-resolution ADCs. The consideration is for a user-centric Cell-Free massive MIMO system, which can reduce the fronthaul load compared to the traditional Cell-Free approach where all APs cooperate to support all users. Most user-centric cell-free massive MIMO research assumes a scenario where the number of APs is much greater than the number of users. In scenarios with a large number of users, a proposed clustering method ensures the connection between APs and users. Each user initially connects to the AP with the largest Large-Scale Fading Coefficient (LSFC). Subsequently, at each AP, a comparison of LSFC among users is performed, and the AP connects to the user with the largest LSFC. The proposed algorithm has confirmed an increase in both the average user spectral efficiency and the sum spectral efficiency when compared to the existing algorithm.