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1 Ergebnisse
1
A Data-Driven Multi-Height Empirical LoS Probability Model ..:
, In:
2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)
,
Zhu, Qiuming
;
Pang, Minghui
;
Wang, Cheng-Xiang
... - p. 1-6 , 2022
Link:
https://doi.org/10.1109/VTC2022-Spring54318.2022.98605..
RT T1 <cTitle>2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)</cTitle>: T1 <Title>A Data-Driven Multi-Height Empirical LoS Probability Model for Urban A2G Channels</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9860586&Exemplar=1&LAN=DE A1 Zhu, Qiuming A1 Pang, Minghui A1 Wang, Cheng-Xiang A1 Lin, Zhipeng A1 Bai, Fei A1 Tian, Yue A1 Mao, Kai A1 Chang, Hengtai YR 2022 SN 2577-2465 K1 Vehicular and wireless technologies K1 Atmospheric modeling K1 Simulation K1 Ray tracing K1 Probability K1 Predictive models K1 Autonomous aerial vehicles K1 line-of-sight (LoS) probability K1 air-to-ground (A2G) mmWave communication K1 unmanned aerial vehicle (UAV) K1 machine learning (ML) SP 1 OP 6 LK http://dx.doi.org/https://doi.org/10.1109/VTC2022-Spring54318.2022.9860586 DO https://doi.org/10.1109/VTC2022-Spring54318.2022.9860586 SF ELIB - SuUB Bremen
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