We give an overview of recent developments in the modeling of radiowave propagation,
based on machine learning (ML) algorithms. We identify the input and output specification …

Driven by the demand to accommodate today's growing mobile traffic, 5G is designed to be
a key enabler and a leading infrastructure provider in the information and communication …

A fully operative and efficient 5G network cannot be complete without the inclusion of
artificial intelligence (AI) routines. Existing 4G networks with all-IP (Internet Protocol) …

Accurate prediction of the large-scale channel fading is fundamental to planning and
optimization in 5G millimeter-wave cellular networks. The current prediction methods, which …

The importance of wireless path loss prediction and interference minimization studies in
various environments cannot be over‐emphasized. In fact, numerous researchers have …

Tabular data and images have been used from machine learning models as two diverse
types of inputs, in order to perform path loss predictions in urban areas. Different types of …

In this letter, we present an alternative procedure for the prediction of propagation path loss
in urban environments, which is based on artificial neural networks (ANNs). The correct …

In the last few years, the mobile data traffic has grown exponentially making evident the
importance of wireless networks. To ensure an acceptable level of quality of service for …

Radio propagation modeling and path loss prediction have been the subject of many
machine learning-based estimation attempts. Our current work uses deep learning for the …

The authors present a machine learning approach for the extraction of radiowave
propagation models in tunnels. To that end, they discuss three challenges related to the …