• DocumentCode
    3600765
  • Title

    On the Accuracy of the High-SNR Approximation of the Differential Entropy of Signals in Additive Gaussian Noise: Real and Complex Cases

  • Author

    Gohary, Ramy H. ; Yanikomeroglu, Halim

  • Author_Institution
    Dept. of Syst. & Comput. Eng., Carleton Univ., Ottawa, ON, Canada
  • Volume
    64
  • Issue
    10
  • fYear
    2015
  • Firstpage
    4845
  • Lastpage
    4850
  • Abstract
    One approach to the analysis of the high signal-to-noise ratio (SNR) capacity of noncoherent wireless communication systems is to ignore the noise component of the received signal in the computation of its differential entropy. In this paper, we consider the error incurred by this approximation when the transmitter and the receiver have one antenna each and when the noise has a Gaussian distribution. We consider the complex and real cases, and we show that when the probability density function (pdf) of the signal component of the received signal is piecewise differentiable, the approximation error decays as 1/SNR, which tightens the available result that the error decays as o(1). In addition, we consider the special instance in which the signal component of the received signal corresponds to a signal transmitted over a channel with a Gaussian fading coefficient. For that case, we provide explicit expressions for the first nonconstant term of the Taylor expansion of the differential entropy, and we invoke Schwartz´s inequality to obtain an efficiently computable bound on it. Our results are supported by numerical examples.
  • Keywords
    Gaussian distribution; Gaussian noise; antennas; approximation theory; fading; radiocommunication; 1/SNR; Gaussian distribution; Gaussian fading coefficient; SNR capacity; Schwartz inequality; Taylor expansion; additive Gaussian noise; approximation error decays; differential signal entropy; high SNR approximation; noise component; noncoherent wireless communication systems; piecewise differentiable; probability density function; signal-to-noise ratio capacity; Approximation methods; Entropy; Random variables; Receivers; Signal to noise ratio; Taylor series; Differential entropy; Lebesgue dominated convergence; sum and product of random variables;
  • fLanguage
    English
  • Journal_Title
    Vehicular Technology, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9545
  • Type

    jour

  • DOI
    10.1109/TVT.2014.2366911
  • Filename
    6945329