DRL-Based Dynamic Resource Allocation for Multi-Beam Satellite Systems
Author:
Affiliation:
1. Chongqing University of Posts and Telecommunications,School of Communication and Information Engineering,Chongqing,P.R. China,400065
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10293227/10293746/10293942.pdf?arnumber=10293942
Reference10 articles.
1. Power Allocation in Multi-User Cellular Networks: Deep Reinforcement Learning Approaches
2. An Elastic Resource Allocation Algorithm based on Dispersion Degree for Hybrid Requests in Satellite Optical Networks
3. Performance of Multibeam Very High Throughput Satellite Systems Based on FSO Feeder Links With HPA Nonlinearity
4. Files Delivery and Share Optimization in LEO Satellite-Terrestrial Integrated Networks: A NOMA Based Coalition Formation Game Approach
5. Dynamic Beam Hopping Method Based on Multi-Objective Deep Reinforcement Learning for Next Generation Satellite Broadband Systems
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