Considerations of Reinforcement Learning within Real-Time Wireless Communication Systems
Author:
Affiliation:
1. Virginia Tech National Security Institute
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10017432/10017302/10017303.pdf?arnumber=10017303
Reference20 articles.
1. Intelligent Anti-Jamming Communication for Wireless Sensor Networks: A Multi-Agent Reinforcement Learning Approach
2. Anti-Jamming Communications Using Spectrum Waterfall: A Deep Reinforcement Learning Approach
3. Pattern-Aware Intelligent Anti-Jamming Communication: A Sequential Deep Reinforcement Learning Approach
4. Dynamic Spectrum Anti-Jamming in Broadband Communications: A Hierarchical Deep Reinforcement Learning Approach
5. An Intelligent Anti-Jamming Scheme for Cognitive Radio Based on Deep Reinforcement Learning
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3. Joint Sub-Band and Transmission Rate Selection for Anti-Jamming Non-Contiguous Orthogonal Frequency Division Multiplexing System: An Upper Confidence Bound Based Reinforcement Learning Approach;Electronics;2023-10-26
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