An overview of machine learning techniques for radiowave propagation modeling
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 …
based on machine learning (ML) algorithms. We identify the input and output specification …
Toward physics-based generalizable convolutional neural network models for indoor propagation
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 …
ability to predict output quantities of interest (such as fields and scattering parameters) in …
Artificial neural network models for radiowave propagation in tunnels
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 …
propagation models in tunnels. To that end, they discuss three challenges related to the …
Generalisable convolutional neural network model for radio wave propagation in tunnels
Propagation models are essential for the prediction of received signal strength and the
planning of wireless systems in a given environment. The vector parabolic equation (VPE) …
planning of wireless systems in a given environment. The vector parabolic equation (VPE) …
Integrating physics-based wireless propagation models and network protocol design for train communication systems
Physics-based wireless propagation modeling and network protocol design have evolved
over decades as orthogonal areas in communication systems research. This fragmented …
over decades as orthogonal areas in communication systems research. This fragmented …
Physics-based optimization of access point placement for train communication systems
Communication-based train-control (CBTC) systems are aimed at replacing conventional
rail signaling with train control enabled by wireless communication between the train and a …
rail signaling with train control enabled by wireless communication between the train and a …
Fast radio-wave propagation modeling in tunnels with a hybrid vector parabolic equation/waveguide mode theory method
Radio-wave propagation modeling in tunnels plays an important role in designing reliable
train communication systems. In recent years, various channel modeling techniques have …
train communication systems. In recent years, various channel modeling techniques have …
Path loss model for 3.5 GHz and 5.6 GHz bands in cascaded tunnel environments
J Qian, Y Wu, A Saleem, G Zheng - Sensors, 2022 - mdpi.com
An important and typical scenario of radio propagation in a railway or subway tunnel
environment is the cascaded straight and curved tunnel. In this paper, we propose a joint …
environment is the cascaded straight and curved tunnel. In this paper, we propose a joint …
Statistical modeling of electromagnetic wave propagation in tunnels with rough walls using the vector parabolic equation method
The vector parabolic equation (VPE) method is a very efficient methodology for high-fidelity
modeling of electromagnetic wave propagation. While the VPE has been widely applied to …
modeling of electromagnetic wave propagation. While the VPE has been widely applied to …
Efficient radio wave propagation modeling in tunnels with a sparse fourier transform-based split-step parabolic equation method
With the emergence of fifth-generation (5G) and beyond wireless systems deployed along
the railway, there is an increasing need for efficient propagation models in tunnels. The …
the railway, there is an increasing need for efficient propagation models in tunnels. The …