Discretized Urban Path Loss Modeling at 3.5 GHz Using Geospatial Features and Machine Learning Techniques: From Regression to Classification

Accurately modeling and predicting urban path loss is a challenging task due to the fact that conventional regression models yield continuous estimates that can hide important performance nuances across different attenuation regimes. Therefore, this study aims to transform the continuous path loss p...

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Główni autorzy:	Jose Lorente-Lopez, Ignacio Rodriguez-Rodriguez, Jose-Victor Rodriguez, Jose Maria Molina-Garcia-Pardo
Format:	Artigo
Język:	Inglês
Wydane:	IEEE 2025-01-01
Seria:	IEEE Access
Hasła przedmiotowe:	Machine learning techniques path-loss prediction radio wave propagation models urban environments
Dostęp online:	https://ieeexplore.ieee.org/document/11202414/
Etykiety:	Dodaj etykietę Nie ma etykietki, Dołącz pierwszą etykiete!