Handover Decision Making for Dense HetNets: A Reinforcement Learning Approach

Handover Decision Making for Dense HetNets: A Reinforcement Learning Approach

In this paper, we consider the problem of decision making in the context of a dense heterogeneous network with a macro base station and multiple small base stations. We propose a deep Q-learning based algorithm that efficiently minimizes the overall energy consumption by taking into account both the...

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Bibliographic Details
Main Authors: Yujae Song, Sung Hoon Lim, Sang-Woon Jeon
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Access
Subjects:
Deep learning
centralized training decentralized execution
energy minimization
heterogeneous networks
load balancing
reinforcement learning
Online Access:https://ieeexplore.ieee.org/document/10064273/

Internet

https://ieeexplore.ieee.org/document/10064273/

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