Troubleshooting of 3G LTE mobility parameters using iterative statistical model refinement

Moazzam Islam Tiwana, Berna Sayrac, Zwi Altman, Tijani Chahed

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a new troubleshooting methodology for 3G Long Term Evolution (LTE) networks based on a closed-form expression between Radio Resource Management (RRM) and Key Performance Indicator (KPI) parameters, using statistical learning. This methodology aims at locally optimising the RRM parameters of the cells with poor performance in an iterative manner. The optimization engine uses the closed-form relationship to calculate the optimized RRM parameters for these cells. The main advantage of this methodolgy is the small number of iterations required to achieve convergence and the QoS objective. A troubleshooting application scenario involving mobility in LTE networks is considered. Numerical simulations illustrate the benefits of our proposed scheme.

Original languageEnglish
Title of host publication2009 2nd IFIP Wireless Days, WD 2009
DOIs
Publication statusPublished - 1 Dec 2009
Externally publishedYes
Event2009 2nd IFIP Wireless Days, WD 2009 - Paris, France
Duration: 15 Dec 200917 Dec 2009

Publication series

Name2009 2nd IFIP Wireless Days, WD 2009

Conference

Conference2009 2nd IFIP Wireless Days, WD 2009
Country/TerritoryFrance
CityParis
Period15/12/0917/12/09

Keywords

  • Automated troubleshooting
  • Handover margin
  • LTE
  • Linear regression
  • Statistical learning

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