Machine-Learning-Based Urban Path Loss Prediction at 900 MHz: Principal Component Analysis, Clustering, Feature Importance and Regression

In this work, the possibility of applying machine learning (ML) techniques to analyze and predict radio wave propagation losses in urban environments is explored. Thus, from a measurement campaign–conducted at 900 MHz in Cartagena, Spain– and the obtaining, by means of digital terrain...

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Autors principals:	Jose Lorente-Lopez, Ignacio Rodriguez-Rodriguez, Jose-Victor Rodriguez, Jose Maria Molina Garcia-Pardo, Juan Aznar-Poveda
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2026-01-01
Col·lecció:	IEEE Open Journal of Antennas and Propagation
Matèries:	Machine learning techniques path-loss prediction radio wave propagation models urban environments
Accés en línia:	https://ieeexplore.ieee.org/document/11231369/
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