Aerial Base Station Positioning and Power Control for Securing Communications: A Deep Q-Network Approach
Author:
Affiliation:
1. Mississippi State University,Department of Electrical and Computer Engineering,USA,MS 39762
2. University of Tennessee,Department of Engineering,Martin,TN,USA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9771381/9771540/09771893.pdf?arnumber=9771893
Reference17 articles.
1. Intelligent Trajectory Design for Secure Full- Duplex MIMO-UAV Relaying Against Active Eavesdroppers: A Model-Free Reinforcement Learning Approach
2. UAV-Enabled Secure Communications by Multi-Agent Deep Reinforcement Learning
3. The Sky Is Not the Limit: LTE for Unmanned Aerial Vehicles
4. Safeguarding 5G wireless communication networks using physical layer security
5. Deep reinforcement learning based computation offloading and resource allocation for MEC
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3. Reinforcement Learning Aided Secure UAV Communications against Roaming Adversaries;2024 International Conference on Information Networking (ICOIN);2024-01-17
4. Multiagent Learning for Secure Wireless Access From UAVs With Limited Energy Resources;IEEE Internet of Things Journal;2023-12-15
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