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2024-07-01
Outage Prediction and Improvement in 6G for UAV Swarm Relays Using Machine Learning
By
Progress In Electromagnetics Research B, Vol. 107, 33-45, 2024
Abstract
The issue of signal outages in sub-THz frequency communication for future 6G networks is addressed by this research. A machine learning method is proposed, employing Random Forest and K-Means algorithms to predict the optimal frequency band and outage probabilities for UAV relays. Both space and frequency diversity are explored to enhance signal strength, and metasurface-carrying UAVs are introduced with a 16 × 16 mm2 design. This design significantly reduces the predicted outage probability from 0.1% to 0.0178%. Finally, triangular and hexagonal UAV swarm formations with metasurfaces are investigated, demonstrating improved performance through heatmap results.
Citation
Hisham Khalil, Gauhar Ali, Saeed Ur Rahman, Muhammad Asim, and Mohammed El Affendi, "Outage Prediction and Improvement in 6G for UAV Swarm Relays Using Machine Learning," Progress In Electromagnetics Research B, Vol. 107, 33-45, 2024.
doi:10.2528/PIERB24031701
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