Multi-Modal Sensing Data-Based Real-Time Path Loss Prediction for 6G UAV-to-Ground Communications
Author:
Affiliation:
1. State Key Laboratory of Advanced Optical Communication Systems and Networks, School of Electronics, Peking University, Beijing, China
2. Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, Jinan, China
Funder
National Natural Science Foundation of China
Taishan Scholars Program
Young Elite Scientists Sponsorship Program by CAST
Natural Science Foundation of Shandong Province
New Cornerstone Science Foundation through the XPLORER PRIZE
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/5962382/10670693/10614105.pdf?arnumber=10614105
Reference18 articles.
1. A General 3D Space-Time-Frequency Non-Stationary Model for 6G Channels
2. A Non-Stationary 3D Model for 6G Massive MIMO mmWave UAV Channels
3. Low‐altitude UAV air‐ground propagation channel measurement and analysis in a suburban environment at 3.9 GHz
4. A UAV-Aided Real-Time Channel Sounder for Highly Dynamic Nonstationary A2G Scenarios
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