Modeling and analysis of device-to-device communications and interference management in heterogeneous cellular networks
Driven by the exponential increase in wireless data traffic, cellular networks are undergoing an unprecedented paradigm shift in the way that data is delivered to the mobile users. The high spectral efficiency and energy efficiency of short-range transmissions make small cell and device-to-device...
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Format: | Theses and Dissertations |
Language: | English |
Published: |
2016
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Online Access: | http://hdl.handle.net/10356/68828 |
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Institution: | Nanyang Technological University |
Language: | English |
Summary: | Driven by the exponential increase in wireless data traffic, cellular networks
are undergoing an unprecedented paradigm shift in the way that data is
delivered to the mobile users. The high spectral efficiency and energy efficiency of short-range transmissions make small cell and device-to-device
(D2D) networks as the key enablers of this shift. In this dissertation, we develop
realistic and tractable analytical frameworks based on random spatial
models (using tools from stochastic geometry) for modeling and analysis of
the fundamental aspects of D2D networks and small cell deployments.
In the context of D2D networks, this dissertation first develops a new
spatial model in which the locations of D2D devices are modeled according
to a Poisson cluster process. Using this model, we study the performance
of a typical D2D receiver in terms of coverage probability and area spectral
efficiency (ASE) for device-centric content placement. Here, the content of
interest is available at the kth closest device from the typical device inside
the same cluster. We discuss in detail the maximum and minimum gains, in
terms of the coverage probability and ASE, achievable in the clustered D2D
networks when such content placement is performed. The developed tools can be used to model various other smart content placement strategies where
the content of interest lies closer to the typical device.
Second, the proposed clustered D2D network model is used to develop
a comprehensive analytical framework that characterizes the performance of
cluster-centric content placement in cache enabled D2D networks. Different
from device-centric content placement, cluster-centric content placement focuses
on placing data in each cluster such that the collective performance of
all the devices in the cluster is optimized. Using this model, we characterize
the performance of the D2D network in terms of coverage probability and
ASE under a variety of cluster-centric content placement strategies.
Third, the cluster-centric analysis demonstrates significant improvement
in the network performance when the device on which content is cached
or device requesting content from a cache is biased to lie (or move) closer
to the cluster center. Based on this insight, we develop and analyze a new
generative double-variance Thomas cluster process model to incorporate such
biased transmissions in the coverage and ASE analysis.
Fourth, in the context of small cell deployments, this dissertation provides
a baseline analytical framework to address the technical aspects of uplink and
downlink communication in hybrid division duplex (HDD)-based two-tier
heterogeneous networks. We propose coordinated interference management
techniques that work in conjunction with uplink power control (in HDD-mode) to enhance the network performance. The effects of the proposed
interference mitigation mechanisms on the whole network are captured by
modeling the locations of transmitters as a Poisson hole process. The analysis
shows significant improvement of the coverage probability under proposed
dynamic interference mitigation. |
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