Deep Reinforcement Learning for Physical Layer Security Enhancement in Energy Harvesting Based Cognitive Radio Networks

Deep Reinforcement Learning for Physical Layer Security Enhancement in Energy Harvesting Based Cognitive Radio Networks

The paper studies the secrecy communication threatened by a single eavesdropper in Energy Harvesting (EH)-based cognitive radio networks, where both the Secure User (SU) and the jammer harvest, store, and utilize RF energy from the Primary Transmitter (PT). Our main goal is to optimize the time slot...

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Bibliographic Details
Main Authors: Ruiquan Lin, Hangding Qiu, Weibin Jiang, Zhenglong Jiang, Zhili Li, Jun Wang
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Sensors
Subjects:
cognitive radio network
energy harvesting
physical layer security
deep reinforcement learning
Online Access:https://www.mdpi.com/1424-8220/23/2/807

Internet

https://www.mdpi.com/1424-8220/23/2/807

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