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. [...]