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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Detalles Bibliográficos
Autores principales: Lin, Ruiquan, Qiu, Hangding, Jiang, Weibin, Jiang, Zhenglong, Li, Zhili, Wang, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9861036/
https://www.ncbi.nlm.nih.gov/pubmed/36679601
http://dx.doi.org/10.3390/s23020807

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9861036/
https://www.ncbi.nlm.nih.gov/pubmed/36679601
http://dx.doi.org/10.3390/s23020807

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