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Experimental Validation of Gaussian Process-Based Air-to-Ground Communication Quality Prediction in Urban Environments

1
Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough, Leicestershire LE11 3TU, UK
2
School of Mechanical, Aerospace and Nuclear Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(14), 3221; https://doi.org/10.3390/s19143221
Received: 26 June 2019 / Revised: 12 July 2019 / Accepted: 17 July 2019 / Published: 22 July 2019
(This article belongs to the Section Sensor Networks)
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Abstract

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. View Full-Text
Keywords: unmanned aerial vehicles; communication relay; gaussian process regression; wireless communication model; urban environment unmanned aerial vehicles; communication relay; gaussian process regression; wireless communication model; urban environment
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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MDPI and ACS Style

Ladosz, P.; Kim, J.; Oh, H.; Chen, W.-H. Experimental Validation of Gaussian Process-Based Air-to-Ground Communication Quality Prediction in Urban Environments. Sensors 2019, 19, 3221.

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