• DocumentCode
    395805
  • Title

    A power control scheme with link gain prediction using PRNN/ERLS for DS-CDMA cellular mobile systems

  • Author

    Hsieh, Yi-Lin ; Chang, Chung-Ju ; Chen, Yih-Shen

  • Author_Institution
    Dept. of Commun. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
  • Volume
    1
  • fYear
    2003
  • fDate
    11-15 May 2003
  • Firstpage
    407
  • Abstract
    In this paper, a link gain prediction-based power control scheme is designed for DS-CDMA cellular mobile systems. The link gain prediction can help to remove the interference of the power control adjustment itself. The pipeline recurrent neural network (PRNN) with extended recursive least square (ERLS) is adopted for the prediction. This PRNN/ERLS predictor possesses infinite memory of past signals so that it can capture precisely the signal correlation and improve the delay compensation of power control. Simulation results show that the link gain prediction-based power control scheme using PRNN/ERLS has lower outage probability than the received SIR prediction-based power control scheme using grey prediction method [S. L. Su, Y. C. Su, and J. F. Huang, November 2000] and improves the system capacity by an amount of 41.6%.
  • Keywords
    cellular radio; code division multiple access; least squares approximations; mobile radio; power control; recurrent neural nets; recursive estimation; spread spectrum communication; telecommunication control; DS-CDMA cellular mobile system; delay compensation; extended recursive least square; link gain prediction; pipeline recurrent neural network; power control scheme; Base stations; Control systems; Delay; Interference; Least squares methods; Multiaccess communication; Pipeline processing; Power control; Predictive models; Recurrent neural networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, 2003. ICC '03. IEEE International Conference on
  • Print_ISBN
    0-7803-7802-4
  • Type

    conf

  • DOI
    10.1109/ICC.2003.1204209
  • Filename
    1204209