Machine-Learning-Based 3-D Channel Modeling for U2V mmWave Communications

Unmanned aerial vehicle (UAV) millimeter wave (mmWave) technologies can provide flexible link and high data rate for future communication networks. By considering the new features of three-dimensional (3-D) scattering space, 3-D velocity, 3-D antenna array, and especially 3-D rotations, a machine le...

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Veröffentlicht in:	IEEE internet of things journal 2022-09, Vol.9 (18), p.17592-17607
Hauptverfasser:	Mao, Kai, Zhu, Qiuming, Song, Maozhong, Li, Hanpeng, Ning, Benzhe, Pedersen, Gert Frolund, Fan, Wei
Format:	Artikel
Sprache:	eng
Schlagworte:	3-D rotations Analytical models Antenna arrays Artificial neural networks Autocorrelation functions Back propagation Back propagation networks backpropagation-based neural network (BPNN) channel generation Channel models channel statistical properties Communication networks Cross correlation Delays generative adversarial network (GAN) Generative adversarial networks Internet of Things Machine learning Mathematical models Millimeter wave communication Millimeter waves Neural networks Parameters Ray tracing Solid modeling Three dimensional models Three-dimensional displays unmanned aerial vehicle (UAV) millimeter wave (mmWave) channel Unmanned aerial vehicles
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