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) …
Comparative Study of VPE-Driven CNN Models for Radio Wave Propagation Modeling in Tunnels
Radio wave propagation modeling in railway environments is of fundamental importance in
designing reliable train communication systems. In recent years, many machine learning …
designing reliable train communication systems. In recent years, many machine learning …
A High-Accuracy Deep Back-Projection CNN-Based Propagation Model for Tunnels
This letter proposes a high-accuracy deep back-projection convolutional neural network
(DBPCNN)-based propagation model for radio wave prediction in long guiding structures …
(DBPCNN)-based propagation model for radio wave prediction in long guiding structures …
Comparative analysis of finite‐difference and split‐step based parabolic equation methods for tunnel propagation modelling
Radio wave propagation modelling in railway environments is of fundamental importance in
designing reliable train communication systems. Parabolic equation (PE) methods have …
designing reliable train communication systems. Parabolic equation (PE) methods have …
Efficient high‐fidelity deep convolutional generative adversarial network model for received signal strength reconstruction in indoor environments
With the rapid development of wireless communication systems, particularly in the era of 5G
and the Internet of Things, deploying wireless communication networks in indoor …
and the Internet of Things, deploying wireless communication networks in indoor …