Publication detail

Optimizing Flying Base Station Connectivity by RAN Slicing and Reinforcement Learning

MELGAREJO, D. POKORNÝ, J. ŠEDA, P. NARAYANAN, A. NARDELLI, P. RASTI, M. HOŠEK, J. ŠEDA, M. RODRÍGUEZ, D. KOUCHERYAVY, Y. FRAIDENRAICH, G.

Original Title

Optimizing Flying Base Station Connectivity by RAN Slicing and Reinforcement Learning

Type

journal article in Web of Science

Language

English

Original Abstract

The application of flying base stations (FBS) in wireless communication is becoming a key enabler to improve cellular wireless connectivity. Following this tendency, this research work aims to enhance the spectral efficiency of FBSs using the radio access network (RAN) slicing framework; this optimization considers that FBSs’ location was already defined previously. This framework splits the physical radio resources into three RAN slices. These RAN slices schedule resources by optimizing individual slice spectral efficiency by using a deep reinforcement learning approach. The simulation indicates that the proposed framework generally outperforms the spectral efficiency of the network that only considers the heuristic predefined FBS location, although the gains are not always significant in some specific cases. Finally, spectral efficiency is analyzed for each RAN slice resource and evaluated in terms of service-level agreement (SLA) to indicate the performance of the framework.

Keywords

Flying Base Stations, UAVs, Location Optimization, Wireless Communication, Deep-reinforcement Learning

Authors

MELGAREJO, D.; POKORNÝ, J.; ŠEDA, P.; NARAYANAN, A.; NARDELLI, P.; RASTI, M.; HOŠEK, J.; ŠEDA, M.; RODRÍGUEZ, D.; KOUCHERYAVY, Y.; FRAIDENRAICH, G.

Released

17. 5. 2022

Publisher

IEEE

ISBN

2169-3536

Periodical

IEEE Access

Year of study

10

Number

1

State

United States of America

Pages from

53746

Pages to

53760

Pages count

15

URL

https://ieeexplore.ieee.org/document/9775679

Full text in the Digital Library

http://hdl.handle.net/11012/208143

BibTex

@article{BUT177853,
  author="Dick Carrillo {Melgarejo} and Jiří {Pokorný} and Pavel {Šeda} and Arun {Narayanan} and Pedro Henrique Juliano {Nardelli} and Mehdi {Rasti} and Jiří {Hošek} and Miloš {Šeda} and Demóstenes Zegarra {Rodríguez} and Yevgeni {Koucheryavy} and Gustavo {Fraidenraich}",
  title="Optimizing Flying Base Station Connectivity by RAN Slicing and Reinforcement Learning",
  journal="IEEE Access",
  year="2022",
  volume="10",
  number="1",
  pages="53746--53760",
  doi="10.1109/ACCESS.2022.3175487",
  issn="2169-3536",
  url="https://ieeexplore.ieee.org/document/9775679"
}