Root Cause Analysis of Reduced Accessibility in 4G Networks - Machine Learning for Networking Access content directly
Conference Papers Year : 2020

Root Cause Analysis of Reduced Accessibility in 4G Networks

Diogo Ferreira
  • Function : Author
  • PersonId : 1102803
Carlos Senna
  • Function : Author
  • PersonId : 1102804
Luís Cortesão
  • Function : Author
  • PersonId : 1102805
Cristina Pires
  • Function : Author
  • PersonId : 1102806
Rui Pedro
  • Function : Author
  • PersonId : 1102807


The increased programmability of communication networks makes them more autonomous, and with the ability to actuate fast in response to users and networks’ events. However, it is usually a difficult task to understand the root cause of the network problems, so that autonomous actuation can be provided in advance.This paper analyzes the probable root causes of reduced accessibility in 4G networks, taking into account the information of important Key Performance Indicators (KPIs), and considering their evolution in previous time-frames. This approach resorts to interpretable machine learning models to measure the importance of each KPI in the decrease of the network accessibility in a posterior time-frame.The results show that the main root causes of reduced accessibility in the network are related with the number of failure handovers, the number of phone calls and text messages in the network, the overall download volume and the availability of the cells. However, the main causes of reduced accessibility in each cell are more related to the number of users in each cell and its download volume produced. The results also show the number of PCA components required for a good prediction, as well as the best machine learning approach for this specific use case.
Fichier principal
Vignette du fichier
487577_1_En_9_Chapter.pdf (501.46 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03266468 , version 1 (21-06-2021)





Diogo Ferreira, Carlos Senna, Paulo Salvador, Luís Cortesão, Cristina Pires, et al.. Root Cause Analysis of Reduced Accessibility in 4G Networks. 2nd International Conference on Machine Learning for Networking (MLN), Dec 2019, Paris, France. pp.117-133, ⟨10.1007/978-3-030-45778-5_9⟩. ⟨hal-03266468⟩
81 View
112 Download



Gmail Facebook X LinkedIn More