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Mobility-Aware Federated Learning-based Proactive UAVs Placement in Emerging Cellular Networks
  • Sanaullah Manzoor,
  • Mazen Hasna,
  • Muhammad Zeeshan Shakir
Sanaullah Manzoor
School of Computing, Engineering, and Physical Sciences, University of West Scotland

Corresponding Author:[email protected]

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Mazen Hasna
College of Engineering, Qatar University
Muhammad Zeeshan Shakir
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With the vast proliferation of smart mobile devices, there is an ever-increasing demand for higher data rates and seamless connectivity throughout. Current 5th generation and beyond (B5G) cellular networks struggle to eradicate outage zones and ensure seamless connectivity. One promising solution to this problem is the use of unmanned aerial vehicles (UAVs) to assist the traditional ground network and provide connectivity in places where there are no small base stations or faulty ones as a result of some natural disasters such as flooding. In this paper, we propose a mobility-aware federated learning-based proactive UAV placement (MFPUP) framework to assist the existing ground communication network and minimize overall network outages. Our MFPUP framework utilizes the federated learning-based mobility prediction model that recommends the potential outage areas to deploy UAVs using user-UAV association techniques such as the optimum association approach (OAP) and the greedy association approach (GAP). In order to validate the performance of the proposed MFPUP scheme we carried out extensive simulations. Our results show that the proposed MFPUP framework associates the optimal number of users to UAVs while also significantly improving users' downlink rates.
26 Mar 2024Submitted to TechRxiv
30 Mar 2024Published in TechRxiv