Dynamic TT&C Mission Scheduling for Mega-Satellite Networks: A Deep Reinforcement Learning Approach
Author:
Affiliation:
1. Xidian University,State Key Laboratory of Integrated Service Networks,Xi'an,Shaanxi,China,710071
Funder
Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10436708/10436716/10437874.pdf?arnumber=10437874
Reference11 articles.
1. 6G Wireless Systems: Vision, Requirements, Challenges, Insights, and Opportunities
2. Coverage enhancement for 6G satellite-terrestrial integrated networks: performance metrics, constellation configuration and resource allocation
3. Ultra-Dense LEO Satellite Based Formation Flying
4. Aerospace Integrated Networks Innovation for Empowering 6G: A Survey and Future Challenges
5. Challenges and Solutions for the Satellite Tracking, Telemetry, and Command System
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. Hierarchical Disturbance Propagation Mechanism and Improved Contract Net Protocol for Satellite TT&C Resource Dynamic Scheduling;Complex System Modeling and Simulation;2024-06
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