• DocumentCode
    1044075
  • Title

    Second-order asymptotics of mutual information

  • Author

    Prelov, Viacheslav V. ; Verdú, Sergio

  • Author_Institution
    Inst. for Problems of Inf. Transmission, Russian Acad. of Sci., Moscow, Russia
  • Volume
    50
  • Issue
    8
  • fYear
    2004
  • Firstpage
    1567
  • Lastpage
    1580
  • Abstract
    A formula for the second-order expansion of the input-output mutual information of multidimensional channels as the signal-to-noise ratio (SNR) goes to zero is obtained. While the additive noise is assumed to be Gaussian, we deal with very general classes of input and channel distributions. As special cases, these channel models include fading channels, channels with random parameters, and channels with almost Gaussian noise. When the channel is unknown at the receiver, the second term in the asymptotic expansion depends not only on the covariance matrix of the input signal but also on the fourth mixed moments of its components. The study of the second-order asymptotics of mutual information finds application in the analysis of the bandwidth-power tradeoff achieved by various signaling strategies in the wideband regime.
  • Keywords
    AWGN channels; channel capacity; covariance matrices; fading channels; information theory; Gaussian additive noise; bandwidth-power tradeoff; channel capacity; covariance matrix; fading channels; fourth mixed moments; low-power communication; multidimensional channels; mutual information; nonlinear channels; second-order asymptotics; signal-to-noise ratio; Additive noise; Covariance matrix; Fading; Gaussian noise; Information analysis; Multidimensional systems; Mutual information; Signal analysis; Signal to noise ratio; Wideband; Channel capacity; fading channels; low-power communication; mutual information; nonlinear channels;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2004.831784
  • Filename
    1317106