Toward Physics-Based Generalizable Convolutional Neural Network Models for Indoor Propagation-Reference-Cited by-同舟云学术

Toward Physics-Based Generalizable Convolutional Neural Network Models for Indoor Propagation

Published:2022-06 Issue:6 Volume:70 Page:4112-4126
ISSN:0018-926X
Container-title:IEEE Transactions on Antennas and Propagation
language:
Short-container-title:IEEE Trans. Antennas Propagat.

Author:

Seretis Aristeidis¹^ORCID,Sarris Costas D.¹^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada

Funder

Natural Sciences and Engineering Research Council of Canada’s (NSERC) Alliance Grant “Enabling Accurate Ray-Tracing Predictions for 5G Communication Channels”

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/8/9794936/09670666.pdf?arnumber=9670666

Reference38 articles.

1. Feature Selective Validation (FSV) for Validation of Computational Electromagnetics (CEM). Part I—The FSV Method

2. Radio propagation prediction model using convolutional neural networks by deep learning;imai;Proc of the European Conf on Antennas and Propag (EuCAP),2019

3. Application of RBF neural networks to the prediction of propagation loss over irregular terrain

4. Field strength prediction in indoor environments with neural networks

Cited by 18 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Efficient Parabolic Equation-Driven CNN Propagation Model in Tunnels Based on Frequency Conversion;IEEE Transactions on Antennas and Propagation;2024-07

2. Electric Field Level Prediction in a Nuclear Power Plant's Main Control Room Using CNN Model;The Journal of Korean Institute of Electromagnetic Engineering and Science;2024-06

3. WiSegRT: Dataset for Site-Specific Indoor Radio Propagation Modeling with 3D Segmentation and Differentiable Ray-Tracing: (Invited Paper);2024 International Conference on Computing, Networking and Communications (ICNC);2024-02-19

4. Measurement-Based Prediction of mmWave Channel Parameters Using Deep Learning and Point Cloud;IEEE Open Journal of Vehicular Technology;2024

5. Physics-informed Generalizable Wireless Channel Modeling with Segmentation and Deep Learning: Fundamentals, Methodologies, and Challenges;IEEE Wireless Communications;2024