The unmanned aerial vehicles (UAVs) are also known as drones. Recently, UAVs have attracted the next generation researchers due to their flexible, dynamic, and cost-effective deployment, etc. Moreover, the UAVs have a wide range of application domains, such as rescue operation in the remote area, military surveillance, emergency application, etc. Given the UAVs are appropriately deployed, the UAVs provide continuous and reliable connectivity, on-demand, and cost-effective features to the desired destination in the wireless communication system. Thus, the UAVs can be a great choice to deploy as a mobile relay in co-existence with the base stations (BSs) on the ground to serve the 5G wireless users. In this thesis, the UAV-assisted mobile relay (UAV-MR) in the next generation wireless networks has been studied, which also considers the UAV-MR physical layer security. The proposed system also considers one ground user, one BS on the ground, and active presence of multiple eavesdroppers, situated nearby the ground user. The locations of these nodes (i.e., the ground user, the BS, and the eavesdroppers) are considered fixed on the ground. Moreover, the locations of the eavesdroppers are not precisely known to the UAV-MR. Thus, this thesis aims to maximize the achievable secrecy rate, while the BS sends the secure information to the ground user via the UAV-MR. However, the UAV-MR has some challenges to deploy in wireless networks, such as 3D deployment, robust resource allocation, secure UAV-MR to ground communication, the channel modeling, the UAV-MR flight duration, and the UAV-MR robust trajectory design, etc. Thus, this project investigates the UAV-MR assisted wireless networks, which addresses those technical challenges to guarantee efficient UAV-MR communication. Moreover, the mathematical frameworks are formulated to support the proposed model. An efficient algorithm is proposed to maximize the UAV-MR achievable secrecy rate. Finally, the simulation results show the improved performance for the UAV-MR assisted next-generation networks.
| Identifer | oai:union.ndltd.org:UTAHS/oai:digitalcommons.usu.edu:etd-8708 |
| Date | 01 August 2019 |
| Creators | Ahmed, Shakil |
| Publisher | DigitalCommons@USU |
| Source Sets | Utah State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | All Graduate Theses and Dissertations |
| Rights | Copyright for this work is held by the author. Transmission or reproduction of materials protected by copyright beyond that allowed by fair use requires the written permission of the copyright owners. Works not in the public domain cannot be commercially exploited without permission of the copyright owner. Responsibility for any use rests exclusively with the user. For more information contact digitalcommons@usu.edu. |
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