• DocumentCode
    945474
  • Title

    Superimposed training for OFDM: a peak-to-average power ratio analysis

  • Author

    Chen, Ning ; Zhou, G. Tong

  • Author_Institution
    Freescale Semicond. Inc., Austin, TX, USA
  • Volume
    54
  • Issue
    6
  • fYear
    2006
  • fDate
    6/1/2006 12:00:00 AM
  • Firstpage
    2277
  • Lastpage
    2287
  • Abstract
    Orthogonal frequency division multiplexing (OFDM) transmission with superimposed training is considered in this paper. One major disadvantage of OFDM is the significant amplitude fluctuations, i.e., high peak-to-average power ratios (PARs). High PARs require large backoff of the average operating power of a radio-frequency (RF) power amplifier (PA) in order to linearly amplify the signal, thus reducing the dc to RF power conversion efficiency. The PAR of the OFDM signal is examined with superimposed training, and its complementary cumulative distribution function (CCDF) is derived. Achievable lower and upper bounds on the CCDF are also determined. In addition, the PAR change is linked to the effective signal-to-noise ratio (SNR) and thus the bit-error-rate (BER) performance under the fixed dc power constraint. Simulation results are presented to illustrate the proposed PAR and power analysis for OFDM with superimposed training.
  • Keywords
    OFDM modulation; error statistics; power amplifiers; radiofrequency amplifiers; signal processing; BER; OFDM; RF power amplifier; SNR; bit-error-rate; complementary cumulative distribution function; orthogonal frequency division multiplexing; peak-to-average power ratio analysis; radio-frequency amplifier; signal-to-noise ratio; Distribution functions; Fluctuations; High power amplifiers; OFDM; Peak to average power ratio; Power conversion; RF signals; Radio frequency; Radiofrequency amplifiers; Upper bound; Orthogonal-frequency-division multiplexing (OFDM); peak-to-average power ratio (PAR); superimposed training;
  • fLanguage
    English
  • Journal_Title
    Signal Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1053-587X
  • Type

    jour

  • DOI
    10.1109/TSP.2006.874299
  • Filename
    1634822