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

Pawel Ladosz, Jongyun Kim, Hyondong Oh, Wen Hua Chen

Research output: Contribution to journalArticlepeer-review

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 languageEnglish
Article number3221
Pages (from-to)1-18
Number of pages18
JournalSensors
Volume19
Issue number14
DOIs
Publication statusPublished - 22 Jul 2019

Keywords

  • communication relay
  • Gaussian process regression
  • unmanned aerial vehicles
  • urban environment
  • wireless communication model

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