arXiv:2409.00050eess.SPcs.CV2024-09被引 10
用机器学习加速毫米波信号覆盖预测，支持任意天线高度的三维建模。
Extending Machine Learning Based RF Coverage Predictions to 3D
- 基于机器学习构建快速信号功率预测模型
- 实现毫米波环境下的实时仿真与高精度估计
- 支持任意发射端高度的三维覆盖预测
本文讨论了在毫米波通信环境中快速预测信号功率的最新进展。利用机器学习（ML），可训练出兼具高精度和实时仿真速度的模型。文中还探讨了改进的训练数据预处理方法以及支持任意发射端高度的三维预测技术。
原文摘要 · Abstract (English)
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.
毫米波信号预测3D建模机器学习
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