• DocumentCode
    1413921
  • Title

    Capacity Results of an Optical Intensity Channel With Input-Dependent Gaussian Noise

  • Author

    Moser, Stefan M.

  • Author_Institution
    Dept. of Electr. Eng., Nat. Chiao Tung Univ. (NCTU), Hsinchu, Taiwan
  • Volume
    58
  • Issue
    1
  • fYear
    2012
  • Firstpage
    207
  • Lastpage
    223
  • Abstract
    This paper investigates a channel model describing optical communication based on intensity modulation. It is assumed that the main distortion is caused by additive Gaussian noise, however, with a noise variance depending on the current signal strength. Both the high-power and low-power asymptotic capacities under simultaneously both a peak-power and an average-power constraint are derived. The high-power results are based on a new firm (nonasymptotic) lower bound and a new asymptotic upper bound. The upper bound relies on a dual expression for channel capacity and the notion of capacity-achieving input distributions that escape to infinity. The lower bound is based on a new lower bound on the differential entropy of the channel output in terms of the differential entropy of the channel input. The low-power results make use of a theorem by Prelov and van der Meulen.
  • Keywords
    Gaussian noise; channel capacity; entropy; intensity modulation; optical communication; additive Gaussian noise; average-power constraint; capacity-achieving input distribution; channel capacity; channel model; differential entropy; high-power asymptotic capacities; input-dependent Gaussian noise; intensity modulation; low-power asymptotic capacities; noise variance; optical communication; optical intensity channel; peak-power constraint; signal strength; Channel capacity; Channel models; Optical noise; Optical receivers; Signal to noise ratio; Upper bound; Channel capacity; Gaussian noise; direct detection; escaping to infinity; high signal-to-noise ratio (SNR); low signal-to-noise ratio (SNR); optical communication;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2011.2169541
  • Filename
    6121996