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Thesis defences

PhD Oral Exam - Moataz Shoukry, Information and Systems Engineering


Date & time
Monday, February 22, 2021 (all day)
Cost

This event is free

Organization

School of Graduate Studies

Contact

Daniela Ferrer

Where

Online

When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.

Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.

Abstract

Aerial platforms and, more precisely, Unmanned Aerial Vehicles (UAVs) or drones augmented with ubiquitous computing, processing and wireless communication technologies are expected to play an important role in next-generation cellular networks. The flexibility, autonomy, altitude adaptiveness, and controllable mobility of UAVs render them suitable to be part of the future wireless access in communication-disabled areas (e.g. disastrous and emergency scenes, mountainous roads, rural and underdeveloped areas, deep amazonic and desert zones, etc). Nonetheless, combined terrestrial and UAV communication networks are capable of substantially improving network coverage and Quality of Service by leveraging line-of-sight communication as well as minimizing the delay and age-of-information for UAV to ground communication. Despite its numerous advantages, the deployment of UAVs faces different challenges with respect to wireless networks, ranging from radio resource management to UAVs’ trajectory under energy limitation constraint and minimal knowledge of the environment. To this end, this dissertation aims to address the challenges in the efficient deployment of UAVs in future networks under various performance metrics. The key goal of this dissertation is to provide the analytical foundations for deployment, learning, in-depth analysis, and optimization of UAV-assisted wireless communication networks. Towards achieving this goal, this dissertation makes significant contributions to several areas of UAV-assisted wireless communication networks within the contexts of static environments as well as high mobility environments. For the deployment of UAVs in static environments such as Internet of Things (IoT) wireless networks, various tools such as optimization theory and machine learning frameworks are employed to enable UAV trajectory design under different scenarios and performance metrics. Results demonstrate the effectiveness of the proposed designs. In particular, UAVs adapt their mobility and altitude to enable reliable and energy efficient communication, to maximize service for IoT applications, and to maintain the freshness of information. For the deployment of UAVs in high mobility environments such as vehicular networks, unique design challenges are considered and carefully handled to guarantee effective performance of the UAV. Particularly, the high mobility of the vehicles leads to distinct network conditions and changes the network topology. The challenge here is that designing an efficient deployment of UAVs while considering the complex and dynamic network conditions is not a trivial task. This challenge was addressed through comprehensive studies that led to effective, robust, and high-performance solutions. Different performance metrics such as coverage, age of information, throughput, and Quality of Service were evaluated and compared with other approaches. Results shed light on the trade-offs in the vehicular network such as throughput-latency when exploiting UAV mobility for service. The findings in this dissertation highlight key guidelines for the effective design of UAV assisted wireless communication networks. More insights on the efficient deployment of UAVs in static and high mobility environments are provided in order to assist and enhance communication in future networks while considering the unique features of UAVs such as their flight time, mobility, energy budget, and altitude.

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