An Aerial Base Station Assignment Algorithm for 5G Networks

• Renata K. G. dos Reis Sidia Institute of Science and Technology / UFPE http://orcid.org/0009-0001-6165-1654
• Maria G. L. Damasceno Sidia Institute of Science and Technology / UFPE https://orcid.org/0009-0009-5586-4053
• Jussif J. A. Arnez Sidia Institute of Science and Technology https://orcid.org/0000-0002-2786-5237
• Caio B. B. de Souza Sidia Institute of Science and Technology / UFPE https://orcid.org/0000-0002-4187-1078
• Andson M. Balieiro UFPE

DOI: https://doi.org/10.5753/w6g.2025.9284

Resumo

Due to network capacity and coverage demands of existing 5G and Beyond 5G networks, Aerial Base Stations (ABS) based on Unmanned Aerial Vehicles (UAV) have been highlighted as a key strategy to expand terrestrial network and assist mobile users. Nevertheless, ABS based on UAV (UAV-BS) are resource constrained in comparison to terrestrial base stations, which implies that resource management procedures are required to efficient UAV-BS operation. In this respect, this work proposes a clustering-based user assignment solution for user to UAV-based ABS, employing a reallocation approach for avoiding connection denial, evaluating the average of allocated users and throughput.

Palavras-chave: 5G Networks, NTN, ABS, UAV, Machine Learning, QoS

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