Application of Machine Learning for Radiowave Propagation Modeling Below 6 GHz

Application of Machine Learning for Radiowave Propagation Modeling Below 6 GHz

This paper presents the application of supervised learning and use of fully connected neural network (FCNN) for the development of a path specific propagation model for frequencies below 6 GHz. The model has been trained and tested against an extensive measurement dataset capturing several areas and...

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Bibliographic Details
Main Authors: Mohammud Z. Bocus, Afzal Lodhi
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Supervised learning
fully connected neural network
multi-layer perceptron
radio path profile
path loss
path-specific prediction methods
Online Access:https://ieeexplore.ieee.org/document/10829601/
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https://ieeexplore.ieee.org/document/10829601/

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