EM DeepRay: An Expedient, Generalizable and Realistic Data-Driven Indoor Propagation Model

Efficient and realistic indoor radio propagation modelling tools are inextricably intertwined with the design and operation of next generation wireless networks. Machine learning (ML)-based radio propagation models can be trained with simulated or real-world data to provide accurate estimates of the...

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Veröffentlicht in:	IEEE transactions on antennas and propagation 2022-06, Vol.70 (6), p.1-1
Hauptverfasser:	Bakirtzis, Stefanos, Chen, Jiming, Qiu, Kehai, Zhang, Jie, Wassell, Ian
Format:	Artikel
Sprache:	eng
Schlagworte:	Coders Computational modeling Data models Decoding deep learning Environment models Frequencies Geometry Indoor environment Indoor environments indoor radio communication Machine Learning Mathematical models Predictive models Propagation radio propagation Radio transmission Ray tracing Wireless networks
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