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Evaluation of Machine Learning Algorithms to Reduce Paging Signalling in a Telecom Network
Linköping University, Department of Computer and Information Science.
Linköping University, Department of Computer and Information Science.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

In a telecommunications network locating user equipment (paging) is a common procedure. Proposed functionality for 4G and 5G allows for eNB initiated paging via X2 interfaces. In this thesis machine learning algorithms were evaluated in order to reduce page signalling. Additionally, two paging schemes based on machine learning were proposed and compared to a common method of paging through cost models. The results show that signalling cost can be reduced by up to 80%.

Place, publisher, year, edition, pages
2017. , p. 89
Keyword [en]
Machine Learning, Telecommunications, Paging, Location Prediction, LTE
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:liu:diva-143714ISRN: LIU-IDA/LITH-EX-A--17/044—SEOAI: oai:DiVA.org:liu-143714DiVA, id: diva2:1166409
Subject / course
Computer Engineering
Examiners
Available from: 2017-12-20 Created: 2017-12-14 Last updated: 2017-12-20Bibliographically approved

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ML_PAGING_TELECOM(2675 kB)74 downloads
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File name FULLTEXT01.pdfFile size 2675 kBChecksum SHA-512
670f367ed6b2c7dffc9c876a4c9928567680967c5653b127c5a58fe03a2ebbd8f816581c122527fc6aae5ce4ffe7109b96dae204be266eecacee2c7866460c94
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Larsson, FredrikKarlsson, Albert
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CiteExportLink to record
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Citation style
  • apa
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Output format
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