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.
Original language | English |
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Article number | 3221 |
Pages (from-to) | 1-18 |
Number of pages | 18 |
Journal | Sensors |
Volume | 19 |
Issue number | 14 |
DOIs | |
Publication status | Published - 22 Jul 2019 |
Keywords
- communication relay
- Gaussian process regression
- unmanned aerial vehicles
- urban environment
- wireless communication model