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

Kai Mao, Qiuming Zhu*, Maozhong Song, Hanpeng Li, Benzhe Ning, Gert Frølund Pedersen, Wei Fan*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

8 Citations (Scopus)
46 Downloads (Pure)


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 learning (ML)-integrated UAV-to-Vehicle (U2V) mmWave channel model is proposed. Meanwhile, an ML-based network for channel parameter calculation and generation is developed. The deterministic parameters are calculated based on the simplified geometry information, while the random ones are generated by the backpropagation-based neural network (BPNN) and generative adversarial network (GAN), where the training data set is obtained from massive ray-tracing (RT) simulations. Moreover, theoretical expressions of channel statistical properties, i.e., power delay profile (PDP), autocorrelation function (ACF), Doppler power spectrum density (DPSD), and cross-correlation function (CCF), are derived and analyzed. Finally, the U2V mmWave channel is generated under a typical urban scenario at 28 GHz. The generated PDP and DPSD show good agreement with RT-based results, which validates the effectiveness of proposed method. Moreover, the impact of 3-D rotations, which has rarely been reported in previous works, can be observed in the generated CCF and ACF, which are also consistent with the theoretical and measurement results.

Original languageEnglish
JournalIEEE Internet of Things Journal
Issue number18
Pages (from-to)17592-17607
Number of pages16
Publication statusPublished - 15 Sep 2022


  • 3D rotations
  • Analytical models
  • BPNN
  • Channel models
  • Delays
  • GAN
  • Internet of Things
  • Millimeter wave communication
  • Solid modeling
  • Three-dimensional displays
  • UAV mmWave channel
  • channel generation
  • channel statistical properties.


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