Computer Vision-Aided mmWave UAV Communication Systems

Zizheng Hua, Yang Lu, Gaofeng Pan, Kun Gao*, Daniel Benevides Da Costa, Su Chen

*Corresponding author for this work

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Abstract

Unmanned aerial vehicle (UAV) communication systems usually operate in harsh scenarios, which require accurate information about the topology and wireless channel to achieve the desired transmission performance. Therefore, when millimeter-wave (mmWave) communication with its intrinsic Line-of-Sight (LoS) condition is adopted, accurate target localization is essential to determine the spatial relationship between the UAV and the grounded receivers (Rxs). In this article, a computer-vision (CV)-aided jointly optimization scheme of flight trajectory and power allocation is designed for mmWave UAV communication systems by utilizing the visual information captured via cameras equipped at the UAV. Compared with traditional schemes, the implementation cost and overhead can be greatly saved as no radio frequency transmissions are required in the proposed localization scheme. In addition, the transmit power at the UAV is jointly optimized with its flight trajectory in two different cases. Finally, simulation results are presented to demonstrate the efficiency of the proposed schemes.

Original languageEnglish
Pages (from-to)12548-12561
Number of pages14
JournalIEEE Internet of Things Journal
Volume10
Issue number14
DOIs
Publication statusPublished - 15 Jul 2023

Keywords

  • Computer vision
  • deep learning
  • energy efficiency
  • trajectory optimization
  • unmanned aerial vehicle (UAV) communication

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Hua, Z., Lu, Y., Pan, G., Gao, K., Costa, D. B. D., & Chen, S. (2023). Computer Vision-Aided mmWave UAV Communication Systems. IEEE Internet of Things Journal, 10(14), 12548-12561. https://doi.org/10.1109/JIOT.2023.3251377