Assessment of Deep Learning Methodology for Self-Organizing 5G Networks

Assessment of Deep Learning Methodology for Self-Organizing 5G Networks

In this paper, we present an auto-encoder-based machine learning framework for self organizing networks (SON). Traditional machine learning approaches, for example, K Nearest Neighbor, lack the ability to be precisely predictive. Therefore, they can not be extended for sequential data in the true se...

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Bibliographic Details
Main Authors: Muhammad Zeeshan Asghar, Mudassar Abbas, Khaula Zeeshan, Pyry Kotilainen, Timo Hämäläinen
Format: Article
Language:English
Published: MDPI AG 2019-07-01
Series:Applied Sciences
Subjects:
deep learning (DL)
self-organizing networks (SON)
5G
autoencoder (AE)
mobility load balancing (MLB)
cell outage detection
intrusion detection
Online Access:https://www.mdpi.com/2076-3417/9/15/2975

Internet

https://www.mdpi.com/2076-3417/9/15/2975

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