Physics-Inspired Machine Learning for Radiomap Estimation: Integration of Radio Propagation Models and Artificial Intelligence
Author:
Affiliation:
1. University of Louisiana at Lafayette,USA
2. Johns Hopkins University,Applied Physics Laboratory,USA
3. University of California at Davis,USA
Funder
University of Louisiana at Lafayette Research Fund
National Science Foundation
Johns Hopkins University Applied Physics Internal Research and Development funds
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/35/10634036/10634040.pdf?arnumber=10634040
Reference15 articles.
1. Radio Map Estimation: A data-driven approach to spectrum cartography
2. Engineering Radio Maps for Wireless Resource Management
3. Radiomap Inpainting for Restricted Areas Based on Propagation Priority and Depth Map
4. RME-GAN: A Learning Framework for Radio Map Estimation Based on Conditional Generative Adversarial Network
5. Minimization of drive tests solution in 3GPP
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