• DocumentCode
    3517692
  • Title

    Real-time issues of predictive modeling for industrial cognitive radios

  • Author

    Ahmad, Kaleem ; Shrestha, Ganesh M. ; Meier, Uwe

  • Author_Institution
    Inst. Ind. IT OWL, Univ. of Appl. Sci., Lemgo, Germany
  • fYear
    2011
  • fDate
    26-29 July 2011
  • Firstpage
    105
  • Lastpage
    110
  • Abstract
    Cognitive radios (CR) can sense and detect temporarily available spectral holes for an opportunistic operation to improve the spectral efficiency and coexistence of industrial radio systems. It will be of particular interest for a CR system to apply predictive modeling in order to forecast the behavior of the coexisting environment. A secondary cognitive user shall use preemptive tuning of its operating parameters following the predictive model. However, a considerable challenge is to generate an accurate model and predict efficiently in order to meet strict time related requirements of industrial applications. Such predictive modeling has already gained some attention but real-time results are never reported. In this contribution we investigate real-time aspects of predictive modeling for its application in industrial CR systems.
  • Keywords
    cognitive radio; CR system; industrial cognitive radios; predictive modeling; secondary cognitive user; Data models; Hidden Markov models; Predictive models; Quality of service; Real time systems; Sensors; Switches;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial Informatics (INDIN), 2011 9th IEEE International Conference on
  • Conference_Location
    Caparica, Lisbon
  • Print_ISBN
    978-1-4577-0435-2
  • Electronic_ISBN
    978-1-4577-0433-8
  • Type

    conf

  • DOI
    10.1109/INDIN.2011.6034845
  • Filename
    6034845