• DocumentCode
    2382448
  • Title

    GM-PAB: A grid-based energy saving scheme with predicted traffic load guidance for cellular networks

  • Author

    Li, Rongpeng ; Zhao, Zhifeng ; Wei, Yan ; Zhou, Xuan ; Zhang, Honggang

  • Author_Institution
    York-Zhejiang Lab. for Cognitive Radio & Green Commun., Zhejiang Univ., Hangzhou, China
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    1160
  • Lastpage
    1164
  • Abstract
    In cellular networks, the base station power consumption is not simply proportional to the traffic loads of its coverage. As the traffic load fluctuates spatially and temporally, the base stations consequently suffer from heavy energy wastage when the traffic loads of their coverage are low. In this paper, we propose a grid-based energy saving scheme over predicted traffic loads. We firstly take advantage of the spatial-temporal pattern of traffic loads and employ the compressed sensing method to predict the future traffic loads. Then, we propose a grid-based energy saving scheme to improve the energy efficiency through turning some base stations into sleeping mode while ensuring the quality of service. Results of the simulation with real traffic loads1 finally show the accuracy of the traffic load prediction and large energy efficiency improvement.
  • Keywords
    cellular radio; compressed sensing; energy conservation; quality of service; telecommunication traffic; GM-PAB; base station power consumption; base stations; cellular networks; compressed sensing method; energy efficiency improvement; grid-based energy saving scheme; heavy energy wastage; predicted traffic load guidance; quality of service; sleeping mode; spatial-temporal pattern; traffic load prediction; Base stations; Compressed sensing; Load modeling; Power demand; Prediction algorithms; Predictive models; Sensors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (ICC), 2012 IEEE International Conference on
  • Conference_Location
    Ottawa, ON
  • ISSN
    1550-3607
  • Print_ISBN
    978-1-4577-2052-9
  • Electronic_ISBN
    1550-3607
  • Type

    conf

  • DOI
    10.1109/ICC.2012.6364637
  • Filename
    6364637