User-centric clustering and pilot assignment in cell-free networks : a stochastic optimization approach

Abstract

Current 5G networks, primarily built on the cellular massive MIMO physical layer technology, achieved significant improvement in spectral efficiency as compared to previous generations. Nevertheless, there is always an increasing demand for higher data rates, and more reliable and uniform service. After successful massive MIMO deployments, it has become a natural question, "what will the physical layer in beyond 5G and 6G networks be like?" Cell-free massive MIMO has emerged as a promising physical layer technology for supporting future deployments in beyond 5G and 6G networks. The main concept is to go beyond the cellular paradigm by employing an ultra dense deployment of small-sized multi-antenna access points (APs) which cooperate to serve users in the coverage area, eliminating the notion of boundaries between cells. The cell-free architecture has shown the capability of providing uniform service within the coverage area, while cellular networks suffer from poor performance at cell edges. It also has better ability to manage interference due to cooperation between APs which is not the case in cellular networks with no cooperation. The most practical form of this paradigm is user-centric cell-free massive MIMO. Instead of allowing all the APs to serve all the users in the network, each user is served by a subset of the APs which ensures that network operation is scalable as the number of users grows. The main objective of this thesis is to provide a structured approach to design the cluster of APs that serve each user which is known as the user-centric clustering problem. On the pursuit to solve the clustering problem, there is another problem which is tightly connected to it, the pilot assignment problem. Both problems must be solved together to ensure satisfactory network-wide performance. [...]