• DocumentCode
    3433302
  • Title

    Fixed point implementation for parameters extraction in a digital predistorter using adaptive algorithms

  • Author

    Garcia-Hernandez, Martin ; Prieto-Guerrero, Alfonso ; Laguna-Sanchez, Gerardo Abel ; Mendoza-Valencia, Paulino

  • Author_Institution
    Dept. of Electr. Eng., Autonomous Metropolitan Univ. - Iztapalapa, Iztapalapa, Mexico
  • fYear
    2012
  • fDate
    2-5 July 2012
  • Firstpage
    978
  • Lastpage
    982
  • Abstract
    In this paper, the parameters extraction from the Volterra series to analyze the performance of a Digital Predistorter (DPD), for the Power Amplifier (PA) with memory, is introduced in two different ways: (1) different numerical methods for the parameters extraction and (2) the fixed point numerical format implementation for this numerical method. The parameters in the Volterra Model are typically calculated based on the mean square error criteria. In this paper, we present some alternatives to reduce the complexity, number of operations, and a PA linearization time ,with DPD dealing with OFDM signals. The simulation results show that with the Volterra model, both the LMS and the VSS algorithms are faster and more effective to calculate the parameters and mantain their convergence properties for a 32-bits implementation.
  • Keywords
    OFDM modulation; Volterra series; least mean squares methods; power amplifiers; signal processing; LMS algorithms; OFDM signals; PA linearization time; VSS algorithms; Volterra series model; adaptive algorithms; digital predistorter; fixed point numerical format; mean square error criteria; numerical methods; parameter extraction; power amplifier; Convergence; Kernel; Least squares approximation; Mathematical model; OFDM; Parameter extraction; Predistortion;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Science, Signal Processing and their Applications (ISSPA), 2012 11th International Conference on
  • Conference_Location
    Montreal, QC
  • Print_ISBN
    978-1-4673-0381-1
  • Electronic_ISBN
    978-1-4673-0380-4
  • Type

    conf

  • DOI
    10.1109/ISSPA.2012.6310697
  • Filename
    6310697