Hierarchical Reinforcement Learning Based Resource Allocation for RAN Slicing

Hierarchical Reinforcement Learning Based Resource Allocation for RAN Slicing

As the complexity of wireless mobile networks increases significantly, artificial intelligence (AI) and machine learning (ML) have become key enablers for radio resource management and orchestration. In this paper, we propose a multi-agent reinforcement learning (RL) method for allocating radio reso...

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Bibliographic Details
Main Authors: Hasan Anil Akyildiz, Omer Faruk Gemici, Ibrahim Hokelek, Hakan Ali Cirpan
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
eMBB
network slicing
radio access networks
reinforcement-learning
resource allocation
URLLC
Online Access:https://ieeexplore.ieee.org/document/10540392/

Internet

https://ieeexplore.ieee.org/document/10540392/

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