The ANFIS handover trigger scheme: The Long Term Evolution (LTE) perspective

C. F. Kwong, T. C. Chuah, S. W. Tan

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

5 Citations (Scopus)

Abstract

With the need for better mobility management strategy to manage increasing demand on efficient data delivery to the user, the Long Term Evolution (LTE) has introduced self-organizing networks (SONs) in order to provide autonomous control over the management of the network. It is important to have a 'self-manage' element in the system to provide a 'quick-fix' and thus reduce the need of constant human participation in the optimization process of the LTE's mobility management. The existing handover triggering scheme for LTE is not flexible enough to introduce new performance metrics such as user equipment (UE) speed, network jitter or even cell loading. Such requirements for flexibility can only be fulfilled by using flexible tools such as fuzzy logic schemes with adaptive capability to cope with the changes of the fast paced mobile environment. This paper will introduce the use of the adaptive neuro-fuzzy inference system (ANFIS) to provide not only flexibility to LTE for initial deployment, but also the adaptive capability to optimize the efficiency of the handover algorithm with minimal human interference.

Original languageEnglish
Title of host publicationProceedings of the 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1374-1381
Number of pages8
ISBN (Electronic)9781479920723
DOIs
Publication statusPublished - 4 Sep 2014
Externally publishedYes
Event2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014 - Beijing, China
Duration: 6 Jul 201411 Jul 2014

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584

Conference

Conference2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2014
Country/TerritoryChina
CityBeijing
Period6/07/1411/07/14

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Artificial Intelligence
  • Applied Mathematics

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