Ademola Adesokan

Work place: American University of Beirut/Department of Computer Science, Beirut, 1107-2020, Lebanon

E-mail: aaa277@mail.aub.edu

Website:

Research Interests:

Biography

Ademola Adesokan is a second-year master’s student in Computer Science Department at the American University of Beirut. He received a bachelor’s degree in computer science from Federal University Dutsin-ma. His current research interest is in using machine learning models and information retrieval to solve health related issues, claim verification and disaster management problems. He is interested in travels, sports, and social development.

Author Articles
RIS-assisted Coverage Maximization Using Multi-UAVs in LTE Networks

By Ademola Adesokan Assaad El Halabi Faten Houjaij

DOI: https://doi.org/10.5815/ijwmt.2023.04.04, Pub. Date: 8 Aug. 2023

In this paper, in order to improve the coverage and the Quality of Service of end-users on the edge of a cellular network, the use of unmanned aerial vehicles (UAVs) is employed to give them direct line of sight. In addition to that, to improve the performance of the said UAVs, reconfigurable intelligent surfaces (RIS) are introduced to the model, in such a way that will enhance the connection of the UAVs with the base station. An RIS will receive a signal from the base station, modulate it and then the RIS will act as the transmitter, sending the signal towards the UAV. By simulating our proposed approach using MATLAB, we have demonstrated that utilizing RIS-assisted communication maximizes coverage between the Base Station and the UAV, outperforming the simulation results of coverage as a function of height without the use of RIS. The significance of this work lies in its ability to enhance the signal quality and coverage at cell edges by leveraging UAVs as intermediate relays. These UAVs serve the purpose of connecting users with weak or no links, effectively bridging the gap. In our simulation results, we employed RIS to strengthen the backhaul link quality between the UAVs and base stations. While our work successfully addresses the challenges of connectivity and coverage, it is important to note that we have not specifically focused on the cost aspect of these factors.

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