Exploiting Future Radio Resources With End-to-End Prediction by Deep Learning

Exploiting Future Radio Resources With End-to-End Prediction by Deep Learning

Machine learning is a powerful tool to predict user behavior and harness the vast amount of data measured in cellular networks. Predictive resource allocation is a promising approach to take advantage of the prediction for the mobility and traffic load related user behavior. This paper strives to bo...

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Bibliographic Details
Main Authors: Jia Guo, Chenyang Yang, I. Chih-Lin
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
User behavior information
radio resource allocation
deep learning
end-to-end prediction
Online Access:https://ieeexplore.ieee.org/document/8543484/

Internet

https://ieeexplore.ieee.org/document/8543484/

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