Air-to-Ground Path Loss Model at 3.6 GHz under Agricultural Scenarios Based on Measurements and Artificial Neural Networks

Hanpeng Li, Kai Mao, Xuchao Ye, Taotao Zhang, Qiuming Zhu, Manxi Wang, Yurao Ge, Hangang Li, Farman Ali

Open source

DOI
10.3390/drones7120701
Published
12
Container
Drones
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.3390/drones7120701,
  title = {Air-to-Ground Path Loss Model at 3.6 GHz under Agricultural Scenarios Based on Measurements and Artificial Neural Networks},
  author = {Hanpeng Li and Kai Mao and Xuchao Ye and Taotao Zhang and Qiuming Zhu and Manxi Wang and Yurao Ge and Hangang Li and Farman Ali},
  year = {2023},
  journal = {Drones},
  doi = {10.3390/drones7120701},
  url = {https://doi.org/10.3390/drones7120701}
}

RIS

TY  - JOUR
TI  - Air-to-Ground Path Loss Model at 3.6 GHz under Agricultural Scenarios Based on Measurements and Artificial Neural Networks
AU  - Hanpeng Li
AU  - Kai Mao
AU  - Xuchao Ye
AU  - Taotao Zhang
AU  - Qiuming Zhu
AU  - Manxi Wang
AU  - Yurao Ge
AU  - Hangang Li
AU  - Farman Ali
PY  - 2023
JO  - Drones
DO  - 10.3390/drones7120701
UR  - https://doi.org/10.3390/drones7120701
ER  - 

APA

Li, H., Mao, K., Ye, X., Zhang, T., Zhu, Q., Wang, M., Ge, Y., Li, H., & Ali, F. (2023). Air-to-Ground Path Loss Model at 3.6 GHz under Agricultural Scenarios Based on Measurements and Artificial Neural Networks. Drones. https://doi.org/10.3390/drones7120701

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