• DocumentCode
    2780595
  • Title

    Automatic Neighbor Relation Penetration Probability Prediction

  • Author

    Li, Yingzhe ; Ji, Li ; Yang, Li

  • Author_Institution
    Wireless Network Res. Dept., Huawei Technol. Co., Ltd., Shanghai, China
  • fYear
    2012
  • fDate
    3-6 Sept. 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Automated configuration of neighbor cell lists, the so-called Automatic Neighbor Relation (ANR) function, is one of the first SON features being deployed in commercial networks. From the operators´ point of view, it is beneficial to know how many ANR enabled UEs should be activated to help the full ANR list configuration. In other words, it is important to predict, given a fixed percentage of ANR enabled UEs, how much time is needed to finish the establishment of neighbor relation list. In this work, we defined an ANR penetration probability prediction method and use this method to, calculate the probability of UE detecting a neighbor relationship based on the number of ANR capable UE number and other related network parameters which can be obtained from the network operators. Two prediction cases using this method are discussed and we use simulation to validate the prediction results.
  • Keywords
    Long Term Evolution; cellular radio; probability; ANR list configuration; ANR penetration probability prediction; Long Term Evolution; UE; automatic neighbor relation; neighbor cell lists; neighbor relation list; network operators; user equipments; Computer architecture; Microprocessors; Predictive models; Probability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Vehicular Technology Conference (VTC Fall), 2012 IEEE
  • Conference_Location
    Quebec City, QC
  • ISSN
    1090-3038
  • Print_ISBN
    978-1-4673-1880-8
  • Electronic_ISBN
    1090-3038
  • Type

    conf

  • DOI
    10.1109/VTCFall.2012.6398918
  • Filename
    6398918