Research Information System
2019 International Conference on Advances in the Emerging Computing Technologies, AECT 2019, AlMadinah, AlManawarrah, Saudi Arabia, 10 February 2020, (Full Text)
© 2020 IEEE.Unmanned aerial vehicles (UAVs) are expected to be deployed in a variety of applications in future mobile networks due to several advantages they bring over the deployment of ground base stations. However, despite the recent interest in UAVs in mobile networks, some issues still remain, such as determining the placement of multiple UAVs in different scenarios. In this paper we propose a solution to determine the optimal 3D position of multiple UAVs in a capacity enhancement use-case, or in other words, when the ground network cannot cope with the user traffic demand. For this scenario, real data from the city of Milan, provided by Telecom Italia is utilized to simulate an event. Based on that, a solution based on k-means, a machine learning technique, to position multiple UAVs is proposed and it is compared with two other baseline methods. Results demonstrate that the proposed solution is able to significantly outperform other methods in terms of users covered and quality of service.