Channel Access and Power Control for Energy-Efficient Delay-Aware Heterogeneous Cellular Networks for Smart Grid Communications Using Deep Reinforcement Learning

Channel Access and Power Control for Energy-Efficient Delay-Aware Heterogeneous Cellular Networks for Smart Grid Communications Using Deep Reinforcement Learning

Cellular technology with long-term evolution (LTE)-based standards is a preferable choice for smart grid neighborhood area networks due to its high availability and scalability. However, the integration of cellular networks and smart grid communications puts forth a significant challenge due to the...

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Bibliographic Details
Main Authors: Fauzun Abdullah Asuhaimi, Shengrong Bu, Paulo Valente Klaine, Muhammad Ali Imran
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Energy efficiency
end-to-end delay
device-to-device communications
cellular networks
smart grids
Online Access:https://ieeexplore.ieee.org/document/8826278/

Internet

https://ieeexplore.ieee.org/document/8826278/

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