A Machine Learning-Based Uplink Resource Allocation Technique for Mixed Traffic in Non-Terrestrial Networks-Reference-Cited by-同舟云学术

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A Machine Learning-Based Uplink Resource Allocation Technique for Mixed Traffic in Non-Terrestrial Networks

Published:2024-06-24 Issue: Volume: Page:23-29
ISSN:
Container-title:2024 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)
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Author:

Abdel-Kader Mohamed¹,Karmoose Mohammed¹,Aboelwafa Mariam²,Gadallah Yasser³,Kheirallah Hassan N.¹

Affiliation:

1. Alexandria University,Department of Communications and Electronics Engineering,Alexandria,Egypt,21544

2. New Giza University,Department of Computer, Communications and Autonomous Systems,Giza,Egypt,12573

3. The American University in Cairo,Department of Electronics and Communications Engineering,New Cairo,Egypt,11835

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10646183/10646188/10646311.pdf?arnumber=10646311

Reference18 articles.

1. A survey on the role of UAVs in the communication process: A technological perspective

2. Machine Learning-Based Multi-UAV Deployment for Uplink Traffic Sizing and Offloading in Cellular Networks

3. Toward Massive, Ultrareliable, and Low-Latency Wireless Communication With Short Packets

4. Resource Allocation of URLLC and eMBB Mixed Traffic in 5G Networks: A Deep Learning Approach

5. Age of Information: An Introduction and Survey

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