• DocumentCode
    2293361
  • Title

    Controlling self healing cellular networks using fuzzy logic

  • Author

    Saeed, Arsalan ; Aliu, Osianoh Glenn ; Imran, Muhammad Ali

  • Author_Institution
    Centre for Commun. Syst. Res., Univ. of Surrey, Guildford, UK
  • fYear
    2012
  • fDate
    1-4 April 2012
  • Firstpage
    3080
  • Lastpage
    3084
  • Abstract
    Wireless cellular communication networks is undergoing a transition from being a simply optional voice communication to becoming a necessity in our everyday lives. In order to ensure uninterrupted high Quality of Experience for subscribers, network operators must ensure 100% reliability of their networks without any discontinuity either for planned maintenance or breakdown. This paper demonstrates self healing capability to the fault recovery process for each cell. It is proposed to compensate cells in failure by neighboring cells optimizing their coverage with antenna reconfiguration and power compensation resulting in filling the coverage gap and improving the QoS for users. The right choice of these reconfigured parameters is determined through a process involving fuzzy logic control and reinforcement learning. Results show an improvement in the network performance for the area under outage as perceived by each user in the system.
  • Keywords
    cellular radio; fault diagnosis; fault tolerant computing; fuzzy control; learning (artificial intelligence); performance evaluation; quality of service; radio networks; software maintenance; telecommunication control; telecommunication network reliability; voice communication; QoS; antenna reconfiguration; breakdown; coverage gap; fault recovery process; fuzzy logic control; neighboring cells; network operators; network performance; network reliability; optional voice communication; planned maintenance; power compensation; quality of experience; reconfigured parameters; reinforcement learning; self healing capability; self healing cellular networks control; wireless cellular communication networks; Fuzzy logic; Interference; Learning; Mathematical model; Signal to noise ratio; Transmitting antennas;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wireless Communications and Networking Conference (WCNC), 2012 IEEE
  • Conference_Location
    Shanghai
  • ISSN
    1525-3511
  • Print_ISBN
    978-1-4673-0436-8
  • Type

    conf

  • DOI
    10.1109/WCNC.2012.6214334
  • Filename
    6214334