الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
Heterogeneous networks (HetNets), device-to-device communications networks (D2D), and unmanned 5G wireless networks are all investigated in this thesis (UAVs). HetNets, which are made up of macro and small cells, have become more common in current wireless networks and 5G systems to meet the rising need for higher data transmission. There are new difficulties in power transmission discrepancies across various basic types of cells (BSs), the somewhat random employment of SBSs, and network densification in compared to classic cell networks, such as macro-small loads and severe intercell interference. This technique is proposed to cache popular store material for BSs and user devices to minimize repetitive wireless transfers, in contrast to the rising number of tablets and smartphones.
Coverage is a major issue for future generations of mobile communication, especially in five-ground networks, where performance expectations have grown, requiring service providers to construct additional stations. Despite the fact that this extra deployment is not cost-effective, it does necessitate network changes. Integration of Unmanned Aerial Vehicles (UAVs) into the current communication infrastructure might readily alleviate this problem. As a result of this challenge, an intelligent solution for the correct and effective use of UAVs in demand areas is given, therefore increasing wireless network capacity and coverage. To address the two challenges mentioned in the thesis, the Macro Base Station (MBS) decision problem and the UAV allocation cooperation problem, the solution provided employs priority and entropy approaches. Finally, these solutions define the NTB, allowing UAVs to be precisely matched to areas of interest, resulting in significant improvements in network parameters such as throughput, capability per EU, 5th percentile spectral efficiency, network retardations, and guaranteed interference signal plus noise ratios of 6.3 percent, 16.6 percent, and 55.9%, respectively, and 48.2 perceived per EU.
The usage of microcells, user selection, and drone design criteria are all covered in the thesis (selecting the position of the UAV that minimises the network delay). Following the definition of the requirements, a comprehensive evaluation is conducted to determine the program’s effectiveness. Our findings demonstrate that processing time affects the system’s performance and the time it takes to handle requests, regardless of how the system is configured.
The prototype of a 5G-ready aerial base station will be shown next. The proposed system allows customers to move their drones while they are flying, thanks to advanced optimization technology that improves customer experience by utilizing real-time network data. In UABSs, the use of cellular network metrics has been demonstrated to increase network performance and enable self-orientation.
For numerical analysis, we utilized MATLAB to test our technique through simulation.