2 research outputs found
Network Management and Decision Making for 5G Heterogeneous Networks
Heterogeneous networks (HetNets) will form an integral part of
future cellular communications. With the proper management of
network resources and decisions, the coexistence of small cells
with macro base stations will improve coverage, data rate and
quality of service for users. This thesis investigates critical
issues that will arise in HetNets.
The first half of this thesis studies major consequences of the
disparity between HetNet tier transmit powers, namely that of
interference and load balancing. To reduce the effects of harmful
interference to small cell users arising from powerful macro
transmissions, we first design a precoding matrix in the form of
a generalized inverse, which, unlike conventional precoding
methods, allows the base station to target a user specifically to
reduce its own interference to that user. Even with a transmit
power constraint, the affected user can achieve significant
improvement in its interference reduction at the slightly
compromise of existing macro users.
Next, we study load balancing by showing the benefits of a
dynamic biasing function for cell range expansion over a static
bias value. Our findings indicate that a dynamic bias is a more
intuitive way to prevent small cell overloading, and that
associating closest users first is a preferred association
order.
We conclude our study into load balancing by proposing a new
notion of network balance. We describe how network balance is
different to user fairness, and subsequently define a new metric
called the network balance index which measures the deviation of
the actual base station load distribution with the expected load
distribution. We show using an algorithm that the network balance
index is more useful than fairness in improving sum rate for
clustered networks.
The second half of this thesis explores more advanced
user-centric issues for HetNets. Chapter 5 proposes a user
association scheme that achieves high fairness, and considers
user association behaviour with network dynamics. In order to
reduce the computation needed to re-associate a large network, we
study the probabilities that each user will have to switch
associations when a user or base station enters or leaves. In the
process, we find that a shrinking network has more effect on user
association than a growing one.
Finally, Chapter 6 extends the conventional idea of HetNets to
include device-to-device (D2D) communications. We propose a D2D
decision making framework that more suitably selects D2D modes
for potential D2D pairs by using a two-stage criteria that leads
to fewer incorrect D2D mode selections. Once a suitable D2D mode
is selected, we demonstrate how to determine optimal or
near-optimal power and resource parameters for each mode in order
to maximize sum rate. We present a geometric approach to solving
the co-channel power control problem, and closed form expressions
where possible for orthogonal frequency allocation. Our
comprehensive study validates the potential for D2D integration
in future cellular communications.
The proposed techniques and insights gained from this thesis aims
to illustrate how networks can be better managed and improve
their decision making processes in order to successfully serve
future users