Energy efficiency analysis of Drone Small Cells positioning based on reinforcement learning

Ana Flávia dos Reis; Glauber Brante; Rafaela Parisotto; Richard D. Souza; Paulo H. V. Klaine; João Pedro Battistella; Muhammad A. Imran

doi:10.1002/itl2.166

journal article Jul 01, 2020

Energy efficiency analysis of Drone Small Cells positioning based on reinforcement learning

Ana Flávia dos Reis Glauber Brante

Rafaela Parisotto Richard D. Souza Paulo H. V. Klaine João Pedro Battistella Muhammad A. Imran

Internet Technology Letters Vol. 3 No. 5 · Wiley

View at Publisher Save 10.1002/itl2.166

Abstract

This work proposes an algorithm to optimize the positioning and the transmit power of Drone Small Cells (DSCs) based on Q‐learning, a technique where the agents learn to maximize a given reward. We consider two different rewards in this work, the first focusing on coverage, while the second maximizes the lifetime. Then, the Q‐learning solution determines the best positioning of the DSC in the 3D space, as well as the optimal transmit power. Results show that the optimization of the transmit power is of paramount importance to reduce the outage probability. In addition, we show that the second reward can considerably increase the network lifetime with a small penalty to the coverage.

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Metrics

6

Citations

12

References

Details

Published: Jul 01, 2020
Vol/Issue: 3(5)
License: View

Authors

A

Ana Flávia dos Reis

Federal University of Technology ‐ Paraná (UTFPR) Curitiba Brazil

G

Glauber Brante

Federal University of Technology ‐ Paraná (UTFPR) Curitiba Brazil

R

Rafaela Parisotto

Federal University of Santa Catarina (UFSC) Florianópolis Brazil

R

Richard D. Souza

Federal University of Santa Catarina (UFSC) Florianópolis Brazil

P

Paulo H. V. Klaine

University of Glasgow Glasgow UK

J

João Pedro Battistella

University of Glasgow Glasgow UK

M

Muhammad A. Imran

University of Glasgow Glasgow UK

Funding

Conselho Nacional de Desenvolvimento Cientifico e Tecnologico

Cite This Article

Ana Flávia dos Reis, Glauber Brante, Rafaela Parisotto, et al. (2020). Energy efficiency analysis of Drone Small Cells positioning based on reinforcement learning. Internet Technology Letters, 3(5). https://doi.org/10.1002/itl2.166

Energy efficiency analysis of Drone Small Cells positioning based on reinforcement learning

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