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Game Theory and Meta Learning for Optimization of Integrated Satellite-Drone-Terrestrial-Communication Systems

Emerging integrated satellite-drone-terrestrial communication (ISDTC) technologies are expected to contribute to our life by bringing forth high speed wireless connectivity to every corner of the world. On the one hand, the Internet of Things (IoT) provides connectivity to various physical objects by enabling them to share information and to coordinate decisions. On the other hand, the non-terrestrial components of an ISDTC system, i.e. unmanned aerial vehicles (UAVs), and satellites, can boost the capacity of wireless networks by providing services to hotspots, disaster affected, and rural areas. Despite the several benefits and practical applications of ISDTC technologies, one must address many technical challenges such as, resource management, trajectory design, device cooperation, data routing, and security. The key goal of this dissertation is to develop analytical foundations for the optimization of ISDTC operations, and the deployment of
non-terrestrial networks (NTNs). First, the problem of resource management within ISDTC systems
is investigated for service-effective cooperation among the terrestrial networks and NTNs. The performance of a multi-layer ISDTC system is analyzed within a competitive market setting.Using a novel decentralized algorithm, spectrum resources are allocated to each one of the communication
links, considering the fairness among devices. The proposed algorithm is proved to reach a Walrasian equilibrium, at which the sum-rate of the network is maximized. The results also show that the proposed algorithm can reach the equilibrium with a practical convergence speed. Then, the effective deployment of NTNs under environmental dynamics is investigated using machine learning solutions with meta training capabilities. First, the use of satellites for on-demand coverage to unforeseeable radio access needs is investigated using game theory. The optimal data routing strategies are learned by the satellite system, using a novel reinforcement learning approach with distribution-robust meta training capability. The results show that, the proposed meta training mechanism significantly reduces the learning cost on the satellites, and is guaranteed to reach the maximal service coverage in the system. Next, the problem of control of UAV-carried radio access points under energy constraints is studied. In particular, novel frameworks are proposed to design trajectories for UAVs that seek to deliver data service to distributed, dynamic, and unforeseeable wireless access requests. The results show that the proposed approaches are guaranteed to converge to an optimal trajectory, and can get a faster convergence speed and lower computation cost using decomposition, cross validation and meta learning. Finally, this dissertation looks at the security of an IoT system. In particular, the impact of human intervention on the system security is analyzed under specific resource constraints. Psychological game theory frameworks are proposed to analyze the human psychology and its impact on the security of the system. The results show that the proposed solution can help the defender optimize its connectivity within the IoT system by estimating the attacker's behavior. In summary, the outcomes of this dissertation provide key guidelines for the effective deployment of ISDTC systems. / Doctor of Philosophy / In the past decade, the goal of providing wireless connectivity to all individuals and communities, including the most disadvantaged ones, has become a national priority both in the US and globally. Yet, remarkably, until today, there is still a great portion of the Earth's population who falls out of today's wireless broadband coverage. While people who live in under-developed or rural areas are still in "wireless darkness", communities in megacities often experience below-par wireless service due to their overloaded communication systems. To provide high-speed, reliable wireless connectivity to those on the less-served side of the digital divide, an integrated space-air-ground communication system can be designed. Indeed, airborne and space-based non terrestrial networks (NTNs) can enhance the capacity and coverage of existing wireless cellular networks (e.g., 5G and beyond) by providing supplemental, affordable, flexible, and reliable service to users in rural, disaster affected, and over-crowded areas.
In order to fill the coverage holes and bridge the digital divide, seamless integration among NTNs and terrestrial networks is needed. In particular, when deploying an integrated communication system, one must consider the problems of spectrum management, device cooperation, trajectory design, and data routing within the system. Meanwhile, with the increased exposure to malicious attacks on high altitude platforms and vulnerable IoT devices, the security within the integrated system must be analyzed and optimized for reliable data service.
To overcome all the technological challenges that hinder the realization of global digital inclusion, this dissertation uses techniques from the fields of game theory, meta learning, and optimization theory to deploy, control, coordinate, and manage terrestrial networks and NTNs. The anticipated results show that a properly integrated satellite-drone-terrestrial communication (ISDTC) system can deliver cost-effective, high speed, seamless wireless service to our world.

Identiferoai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/112265
Date01 September 2021
CreatorsHu, Ye
ContributorsElectrical Engineering, Saad, Walid, Reed, Jeffrey H., Clancy, Thomas Charles, Woolsey, Craig A., Kekatos, Vasileios
PublisherVirginia Tech
Source SetsVirginia Tech Theses and Dissertation
Detected LanguageEnglish
TypeDissertation
FormatETD, application/pdf
RightsIn Copyright, http://rightsstatements.org/vocab/InC/1.0/

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