• DocumentCode
    226988
  • Title

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

  • Author

    Kwong, C.F. ; Chuah, Teong Chee ; Tan, S.W.

  • Author_Institution
    Fac. of Sci., Technol., Eng. & Math., INTI Int. Univ., Nilai, Malaysia
  • fYear
    2014
  • fDate
    6-11 July 2014
  • Firstpage
    1374
  • Lastpage
    1381
  • 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.
  • Keywords
    Long Term Evolution; fuzzy neural nets; fuzzy reasoning; mobility management (mobile radio); self-organising feature maps; telecommunication computing; ANFIS handover trigger scheme; LTE; Long Term Evolution; adaptive neuro-fuzzy inference system; autonomous control; handover algorithm efficiency; mobility management; network management; self-organizing networks; Fuzzy logic; Handover; Long Term Evolution; Measurement; Quality of service; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4799-2073-0
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2014.6891808
  • Filename
    6891808