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Framework for Behavioral Analysis of Mobile Networks.

Authors :
Trujillo, José Antonio
de-la-Bandera, Isabel
Palacios, David
Barco, Raquel
Chong, Peter Han Joo
Source :
Sensors (14248220); May2021, Vol. 21 Issue 10, p3347-3347, 1p
Publication Year :
2021

Abstract

The arrival of the Fifth Generation (5G) entails a significant evolution in the context of mobile communication networks. This new technology will bring heterogeneous scenarios with new types of services and an increasingly high number of users and nodes. The efficient management of such complex networks has become an important challenge. To address this problem, automatic and efficient algorithms must be developed to facilitate operators' management and optimization of their networks. These algorithms must be able to cope with a very high number of heterogeneous data and different types of scenarios. In this paper, a novel framework for a cellular network behavioral analysis and monitoring is presented. This framework is based on a combination of unsupervised and supervised machine learning techniques. The proposed system can analyze the behavior of cells and monitor them, searching for behavior changes over time. The information extracted by the framework can be used to improve subsequent management and optimization functions. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14248220
Volume :
21
Issue :
10
Database :
Complementary Index
Journal :
Sensors (14248220)
Publication Type :
Academic Journal
Accession number :
150523285
Full Text :
https://doi.org/10.3390/s21103347