Radiomap Inpainting for Restricted Areas Based on Propagation Priority and Depth Map-Reference-Cited by-同舟云学术

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Radiomap Inpainting for Restricted Areas Based on Propagation Priority and Depth Map

Published:2024-08 Issue:8 Volume:23 Page:9330-9344
ISSN:1536-1276
Container-title:IEEE Transactions on Wireless Communications
language:
Short-container-title:IEEE Trans. Wireless Commun.

Author:

Zhang Songyang¹^ORCID,Yu Tianhang²,Choi Brian³^ORCID,Ouyang Feng³,Ding Zhi²^ORCID

Affiliation:

1. Department of Electrical and Computer Engineering, University of Louisiana at Lafayette, Lafayette, LA, USA

2. Department of Electrical and Computer Engineering, University of California at Davis, Davis, CA, USA

3. The Johns Hopkins University Applied Physics Laboratory, Laurel, MD, USA

Funder

National Science Foundation

University of Louisiana at Lafayette Research Fund

The Johns Hopkins University Applied Physics Laboratory Independent Research and Development Program

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

https://ieeexplore.ieee.org/ielam/7693/10634844/10424680-aam.pdf

Reference48 articles.

1. Radio Map Estimation: A data-driven approach to spectrum cartography

2. Engineering Radio Maps for Wireless Resource Management

3. Deep Learning-based Framework for Multi-Fault Diagnosis in Self-Healing Cellular Networks

4. Radio Map-Based 3D Path Planning for Cellular-Connected UAV

5. Localization and Navigation in Autonomous Driving: Threats and Countermeasures

Cited by 1 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. Physics-Inspired Machine Learning for Radiomap Estimation: Integration of Radio Propagation Models and Artificial Intelligence;IEEE Communications Magazine;2024-08

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