Mobile Edge Computing-Based Data-Driven Deep Learning Framework for Anomaly Detection

Mobile Edge Computing-Based Data-Driven Deep Learning Framework for Anomaly Detection

5G is anticipated to embed an artificial intelligence (AI)-empowerment to adroitly plan, optimize and manage the highly complex network by leveraging data generated at different positions of the network architecture. Outages and situation leading to congestion in a cell pose severe hazard for the ne...

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Bibliographic Details
Main Authors: Bilal Hussain, Qinghe Du, Sihai Zhang, Ali Imran, Muhammad Ali Imran
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Cellular network
anomaly detection
call detail record
deep learning
big data analytics
sleeping cell
Online Access:https://ieeexplore.ieee.org/document/8844663/

Internet

https://ieeexplore.ieee.org/document/8844663/

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