The ever-increasing demand for better mobile experiences is propelling the research
communities to look ahead at how future networks can be geared up to meet
such demands. It is likely that the next-generation of wireless communications will be
revolutionary, outpacing the current systems capabilities in terms connectivity, reliability
and intelligence. These trends and predictions will cause a revolutionary change
in the wireless communications. In this context, the concept of Ultra-Dense Network
(UDN) is poised to be the cornerstone of the development of fifth generation(5G) systems,
whereby a massive number of base stations (BSs) are deployed for enhancing the
network performance metrics. Though such densification might be economically viable
in urban areas, it is mostly unfavorable in rural ones due to the sheer complexity
and the various factors involved the planning and installation processes; all of which
trigger the need for cost-effective, flexible and easily-implementable solutions. As a
result, unmanned aerial vehicles (UAVs) emerge as a promising alternative solution
for enhancing wireless coverage. Due to their mobility capabilities, UAVs are of particular
importance in events of (i) terrestrial-based cellular systems dilapidation, (ii)
infrastructure absence in remote and suburban areas, or (iii) limited-duration events
or activities wherein there is a short-term need for supplementary network resources
to handle the overload. While a growing body literature works towards characterizing
and providing insights into the performance of UAVs-only networks (serving the
first two purposes), understanding the performance of such networks when coupled
with existing terrestrial BSs remains a challenging, yet interesting, open research
venue. Towards this direction, this thesis provides a rigorous analysis of the downlink
coverage probability of hybrid aerial-terrestrial networks using tools from Stochastic
Geometry. The thesis presents a mathematical model that characterizes the coverage
probability metric under different network environments. The proposed model is validated
against intensive simulations so as to substantiate the analytical results. The
developed work is essential to understanding the premises of one possible solution to
the UDNs of tomorrow, capture its key performance metrics and, most importantly, to
uncover key design insights and reveal new directions for the wireless communication
industry.
Date of Award | Dec 2018 |
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Original language | English (US) |
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Awarding Institution | - Computer, Electrical and Mathematical Sciences and Engineering
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Supervisor | Mohamed-Slim Alouini (Supervisor) & Tareq Al-Naffouri (Supervisor) |
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- stochastic geometry
- Unmanned Aerial Vehicle
- Hybird Networks