Deep Learning for Radio Resource Allocation Under DoS Attack
Author:
Affiliation:
1. School of Electrical and Computer Engineering, The University of Sydney, Camperdown, NSW, Australia
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/9882533/10356147/10535299.pdf?arnumber=10535299
Reference34 articles.
1. Deep Reinforcement Learning for Joint Sensor Scheduling and Power Allocation under DoS Attack
2. Self-Unaware Adversarial Multi-Armed Bandits With Switching Costs
3. Multiuser Scheduling in Centralized Cognitive Radio Networks: A Multi-Armed Bandit Approach
4. Redundant Sniffer Deployment for Multi-Channel Wireless Network Forensics With Unreliable Conditions
5. Optimal energy-efficient regular delivery of packets in cyber-physical systems
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