Coverage and Energy Analysis of T-UAV-Assisted Cellular Networks: Stochastic Geometry Approach.
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Committee membersEltawil, Ahmed
Embargo End Date2024-03-06
Permanent link to this recordhttp://hdl.handle.net/10754/690127
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Access RestrictionsAt the time of archiving, the student author of this thesis opted to temporarily restrict access to it. The full text of this thesis will become available to the public after the expiration of the embargo on 2024-03-06.
AbstractAn unmanned aerial vehicle-mounted base station (UAV-BS), also known as an aerial base station (ABS), is a viable technology for the next 6G wireless networks due to its adaptability and affordability. Furthermore, the concept of tethered UAVs (T-UAVs), can be used to circumvent the limited network operating time of UAV-BS networks. T-UAVs are UAVs powered by a ground energy source via a tether that restrain their mobility while providing unlimited power. In this thesis, we propose systems where ABSs are deployed in user hotspots to offload the traffic and assist terrestrial base stations (TBSs). First, we propose three different scenarios based on a model of cluster pairs. We start by determining the optimal locations of T-UAVs that minimize the average pathloss for each scenario. Next, using tools from stochastic geometry and an approach of dividing the space into concentric rings and slices to quantify the locations and orientations of GSs, we analyse both coverage and energy performance for each scenario and compare their performances. We use Monte-Carlo simulations to validate our findings and provide several useful insights. For instance, we show that deploying for each pair of clusters a T-UAV that can be attached and detached from the GS is the best strategy to adopt in terms of both coverage and energy efficiency. Second, we propose a hybrid system composed of tethered and untethered UAVs (T/U-UAVs). We study the coverage performance as a function of some system parameters such as the fraction of T-UAVs that have been used, the U-UAV availability, and the radius of clusters, and we provide useful insights.
CitationKhemiri, S. (2023). Coverage and Energy Analysis of T-UAV-Assisted Cellular Networks: Stochastic Geometry Approach. [KAUST Research Repository]. https://doi.org/10.25781/KAUST-V4VQ9