Deep reinforcement learning for secrecy energy efficiency maximization in RIS-assisted networks

Deep reinforcement learning for secrecy energy efficiency maximization in RIS-assisted networks

This paper investigates the deep reinforcement learning (DRL) for maximization of the secrecy energy efficiency (SEE) in reconfigurable intelligent surface (RIS)-assisted networks. An SEE maximization problem is formulated under constraints of the rate requirement of each (legitimate) user, the powe...

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Bibliographic Details
Main Authors: Zhang, Yichi, Lu, Yang, Zhang, Ruichen, Ai, Bo, Niyato, Dusit
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2023
Subjects:
Engineering::Computer science and engineering
Array Signal Processing
Energy Efficiency
Online Access:https://hdl.handle.net/10356/170813
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Institution: Nanyang Technological University
Language: English

Internet

https://hdl.handle.net/10356/170813

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