Joint User-Centric Clustering and Pilot Allocation for Scalable Cell-Free Massive MIMO System

Abstract

Cell-free massive multiple-input multiple-output (MIMO) is a promising technology where many access points (APs) cooperate to jointly serve user equipments (UEs) within the same time-frequency resource. However, the initial form of cell-free massive MIMO is not scalable when the number of UEs becomes very large. User clustering is a solution that can be used to make the system scalable as the number of UEs increases to infinity because each access point (AP) points progresses signals only from a subset of UEs it serves. The objective of this research is to design a joint user-centric clustering and pilot allocation system for scalable cell-free massive MIMO, which aims to achieve uniform spectral efficiency for all UEs. Therefore, this research aimed to combine the Gale-Shapley clustering algorithm with two existing pilot allocation methods, namely, the scalable and graph-coloring methods. The result showed that with 10 available orthogonal pilots, the scalable pilot allocation method achieves more than twice the 95%-likely spectral efficiency compared to the graph-coloring method. Furthermore, when the number of APs equals UEs, the complexity of the scalable method is linear in the number of UEs, as opposed to the polynomial complexity of the graph-coloring method.

Keywords

• beyond 5g
• cooperative communications
• linear beamforming
• network-centric
• uniform rate