Extending Machine Learning Based RF Coverage Predictions to 3D

Muyao Chen, Mathieu Châteauvert, Jonathan Ethier
8/19/2024
eess.SPcs.CVcs.IT

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Abstract

This paper discusses recent advancements made in the fast prediction of signal power in mmWave communications environments. Using machine learning (ML) it is possible to train models that provide power estimates with both good accuracy and with real-time simulation speeds. Work involving improved training data pre-processing as well as 3D predictions with arbitrary transmitter height is discussed.

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Cite this paper

@article{chen2024extending,
  title  = {Extending Machine Learning Based RF Coverage Predictions to 3D},
  author = {Muyao Chen and Mathieu Châteauvert and Jonathan Ethier},
  year   = {2024},
  eprint = {2409.00050},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2409.00050v1}
}

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