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Experimental validation of gaussian process-based air-to-ground communication quality prediction in urban environments

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posted on 24.10.2019, 10:41 by Pawel Ladosz, Jongyun Kim, Hyondong Oh, Wen-Hua ChenWen-Hua Chen
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This paper presents a detailed experimental assessment of Gaussian Process (GP) regression for air-to-ground communication channel prediction for relay missions in urban environment. Considering restrictions from outdoor urban flight experiments, a way to simulate complex urban environments at an indoor room scale is introduced. Since water significantly absorbs wireless communication signal, water containers are utilized to replace buildings in a real-world city. To evaluate the performance of the GP-based channel prediction approach, several indoor experiments in an artificial urban environment were conducted. The performance of the GP-based and empirical model-based prediction methods for a relay mission was evaluated by measuring and comparing the communication signal strength at the optimal relay position obtained from each method. The GP-based prediction approach shows an advantage over the model-based one as it provides a reasonable performance without a need for a priori information of the environment (e.g., 3D map of the city and communication model parameters) in dynamic urban environments.

Funding

National Research Foundation of Korea (NRF) funded by the Ministry of Education (2017R1D1A1B03029992)

2019 Research Fund (1.190011.01) of UNIST (Ulsan National Institute of Science and Technology).

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

Sensors

Volume

19

Issue

14

Publisher

MDPI AG

Version

VoR (Version of Record)

Rights holder

© the authors

Publisher statement

This is an Open Access Article. It is published by MDPI under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/

Acceptance date

17/07/2019

Publication date

2019-07-22

Copyright date

2019

ISSN

1424-8220

eISSN

1424-8220

Language

en

Location

Switzerland

Depositor

Mr Pawel Ladosz Deposit date: 11 October 2019

Article number

3221