• DocumentCode
    1106687
  • Title

    Volterra-series-based analytic technique to assess the power density spectrum of nonlinearly distorted OFDM signals

  • Author

    Rodrigues, M.R.D. ; Darwazeh, I. ; O´Reilly, J.J.

  • Author_Institution
    Dept. of Eng., Univ. of Cambridge, UK
  • Volume
    151
  • Issue
    4
  • fYear
    2004
  • Firstpage
    401
  • Lastpage
    407
  • Abstract
    A Volterra-series-based analytic technique is developed to assess the power density spectrum of orthogonal frequency division multiplexing (OFDM) signals distorted by frequency-independent or frequency-dependent nonlinearities. The nonlinearly distorted OFDM signal power density spectrum is expressed in terms of the non-distorted OFDM signal harmonic power density spectra and the nonlinearity transfer functions. The effectiveness of the technique in both the frequency-independent and the frequency-dependent cases is established by comparing analysis and simulation. It is shown that if the OFDM signal is modelled rigorously as a cyclostationary stochastic process, analysis agrees perfectly with simulation. Further, it is also shown that if the OFDM signal is modelled as a stationary stochastic process, the developed mathematical expressions reduce to the familiar Bedrosian-Rice expressions. The appropriateness of this approximation for many practical purposes is verified by the very close agreement obtained between the simplified analytic and simulation results.
  • Keywords
    OFDM modulation; Volterra series; nonlinear distortion; nonlinear systems; spectral analysis; stochastic processes; transfer functions; Bedrosian-Rice expression; OFDM; Volterra-series-based analytic technique; cyclostationary stochastic process; frequency-dependent nonlinearity; mathematical expression; orthogonal frequency division multiplexing signal; power density spectrum; transfer function;
  • fLanguage
    English
  • Journal_Title
    Communications, IEE Proceedings-
  • Publisher
    iet
  • ISSN
    1350-2425
  • Type

    jour

  • DOI
    10.1049/ip-com:20040399
  • Filename
    1335442