Transform-Based Multiresolution Decomposition for Unsupervised Learning and Data Clustering of Cellular Network Behavior

The growing complexity of cellular networks makes it harder for network operators to control and manage the system. To ease the management and automatically detect network problems, unsupervised techniques have been put to use. This work proposes a novel method that combines Multi-Resolution Analysi...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Juan Cantizani-Estepa, Sergio Fortes, Javier Villegas, Javier Rasines, Raul Martin Cuerdo, Raquel Barco
Format:	Article
Language:	English
Published:	IEEE 2024-01-01
Subjects:	Anomaly detection cellular networks clustering multiresolution analysis (MRA) Gaussian mixture model (GMM)
Online Access:	https://ieeexplore.ieee.org/document/10763485/