NDLI: Machine Learning Based Session Drop Prediction in LTE Networks and Its SON Aspects

Content Provider	IEEE Xplore Digital Library
Author	Daroczy, B. Vaderna, P. Benczur, A.
Copyright Year	2015
Description	Author affiliation: Inst. for Comput. Sci. & Control, Budapest, Hungary (Daroczy, B.; Benczur, A.) \|\| Manage. & Oper. of Complex Syst., Ericsson Res., Budapest, Hungary (Vaderna, P.)
Abstract	Abnormal bearer session release (i.e. bearer session drop) in cellular telecommunication networks may seriously impact the quality of experience of mobile users. The latest mobile technologies enable high granularity real-time reporting of all conditions of individual sessions, which gives rise to use data analytics methods to process and monetize this data for network optimization. One such example for analytics is Machine Learning (ML) to predict session drops well before the end of session. In this paper a novel ML method is presented that is able to predict session drops with higher accuracy than using traditional models. The method is applied and tested on live LTE data offline. The high accuracy predictor can be part of a SON function in order to eliminate the session drops or mitigate their effects.
Starting Page	1
Ending Page	5
File Size	445431
Page Count	5
File Format	PDF
ISBN	9781479980888
DOI	10.1109/VTCSpring.2015.7145925
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-05-11
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Time series analysis Uplink Interference Support vector machines Kernel Accuracy Signal to noise ratio
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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