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Sequence-based detection of sleeping cell failures in mobile networks

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Abstract

This article presents an automatic malfunction detection framework based on data mining approach to analysis of network event sequences. The considered environment is long term evolution (LTE) of Universal Mobile Telecommunications System with sleeping cell caused by random access channel failure. Sleeping cell problem means unavailability of network service without triggered alarm. The proposed detection framework uses N-gram analysis for identification of abnormal behavior in sequences of network events. These events are collected with minimization of drive tests functionality standardized in LTE. Further processing applies dimensionality reduction, anomaly detection with K-Nearest Neighbors, cross-validation, postprocessing techniques and efficiency evaluation. Different anomaly detection approaches proposed in this paper are compared against each other with both classic data mining metrics, such as F-score and receiver operating characteristic curves, and a newly proposed heuristic approach. Achieved results demonstrate that the suggested method can be used in modern performance monitoring systems for reliable, timely and automatic detection of random access channel sleeping cells.

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Notes

  1. Evolved Universal Terrestrial Radio Access Network (E-UTRAN)

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Acknowledgments

Authors would like to thank colleagues from Magister Solutions, Nokia and University of Jyväskylä for collaboration, their valuable feedback regarding this research, and peer reviews. Work on this study has been partly funded by MIPCOM project, Graduate School in Electronics, Telecommunications and Automation (GETA), and Doctoral Program in Computing and Mathematical Sciences (COMAS).

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  1. Magister Solution Ltd., Sepankatu 14 C, 40720, Jyväskylä, Finland

    Fedor Chernogorov

  2. Department of Mathematical Information Technology, University of Jyvaskyla, P.O. Box 35, 40014, Jyväskylä, Finland

    Fedor Chernogorov, Sergey Chernov, Kimmo Brigatti & Tapani Ristaniemi

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  1. Fedor Chernogorov
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Correspondence to Fedor Chernogorov.

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Chernogorov, F., Chernov, S., Brigatti, K. et al. Sequence-based detection of sleeping cell failures in mobile networks. Wireless Netw 22, 2029–2048 (2016). https://doi.org/10.1007/s11276-015-1087-9

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