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 …

Several orthodox approaches, such as empirical methods and deterministic methods, had
earlier been used for the prediction of path loss in wireless communication systems. These …

Path loss prediction is of great significance for the performance optimization of wireless
networks. With the development and deployment of the fifth-generation (5G) mobile …

Unlimited access to information and data sharing wherever and at any time for anyone and
anything is a fundamental component of fifth-generation (5G) wireless communication and …

Path loss is one of the most important factors affecting base-station positioning in cellular
networks. Traditionally, to determine the optimal installation position of a base station, path …

The need for wider coverage and high-performance quality of mobile networks is critical due
to the maturity of Internet penetration in today's society. One of the primary drivers of this …

This paper presents and assesses various machine learning methods that aim at predicting
path loss in rural environment. For this purpose, models such as artificial neural network …

This paper presents a novel method for radio map construction that simultaneously
interpolates the received signal power values over space and frequency domains. Radio …

Vehicular Visible Light Communication (VVLC) is preferred as a vehicle to everything (V2X)
communications scheme due to its highly secure, low complexity and radio frequency (RF) …

A fundamental challenge for machine learning (ML) models for electromagnetics is their
ability to predict output quantities of interest (such as fields and scattering parameters) in …