User Association in Scalable Cell-Free Massive MIMO Systems

TL;DR

This paper proposes a user-association method for scalable cell-free massive MIMO systems that maximizes sum-rate while reducing backhaul load, using a Hungarian Algorithm based on AP positions.

Contribution

It introduces a novel user-association procedure leveraging the Hungarian Algorithm for scalable cell-free MIMO systems, balancing performance and backhaul load.

Findings

Lower backhaul load compared to full-cell free approaches

Performance close to optimal with negligible loss

Effective in large-scale network scenarios

Abstract

In this work, we consider the uplink of a scalable cell-free massive MIMO system where the users are served only by a subset of access points (APs) in the network. The APs are physically grouped into predetermined "cell-centric clusters", which are connected to different cooperative central processing units (CPUs). Given the cooperative nature of the considered communications network, we assume that each user is associated with a "virtual cluster", that, in general, involves some APs belonging to different cell-centric clusters. Assuming the maximum-ratio-combining at the APs, we propose a user-association procedure aimed at the maximization of the sum-rate of the users in the system. The proposed procedure is based on the Hungarian Algorithm and exploits only the knowledge of the position of the APs in the network. Numerical results reveal that the performance of the proposed approach is not always better than the alternatives but it offers a considerably lower backhaul load with a negligible performance loss compared to full-cell free approaches.