Hybrid Multi-Agent Deep Reinforcement Learning for Active-IRS-Based Rate Maximization Over 6G UAV Mobile Wireless Networks
Author:
Affiliation:
1. Southwest University,College of Electronic and Information Engineering,Chongqing,China,400715
2. Texas A&M University,Networking and Information Systems Laboratory,Department of Electrical and Computer Engineering,College Station,TX,USA,77843
Funder
National Science Foundation
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10356123/10356124/10356357.pdf?arnumber=10356357
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1. Survey on Unmanned Aerial Vehicle Networks for Civil Applications: A Communications Viewpoint
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3. Cross-layer-based modeling for quality of service guarantees in mobile wireless networks
4. Quality-of-Service Driven Power and Rate Adaptation over Wireless Links
5. Cross-Layer Based Opportunistic MAC Protocols for QoS Provisionings Over Cognitive Radio Wireless Networks
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