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: Lin, Ruiquan, Qiu, Hangding, Jiang, Weibin, Jiang, Zhenglong, Li, Zhili, Wang, Jun
Other Authors: School of Electrical and Electronic Engineering
Format: Journal Article
Language:English
Published: 2023
Subjects:
Engineering::Electrical and electronic engineering
Cognitive Radio Network
Energy Harvesting
Online Access:https://hdl.handle.net/10356/169461

Internet

https://hdl.handle.net/10356/169461

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