• DocumentCode
    37509
  • Title

    Gaussian Channel With Noisy Feedback and Peak Energy Constraint

  • Author

    Yu Xiang ; Young-Han Kim

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Univ. of California, San Diego, La Jolla, CA, USA
  • Volume
    59
  • Issue
    8
  • fYear
    2013
  • fDate
    Aug. 2013
  • Firstpage
    4746
  • Lastpage
    4756
  • Abstract
    Optimal coding over the additive white Gaussian noise channel under the peak energy constraint is studied when there is noisy feedback over an orthogonal additive white Gaussian noise channel. As shown by Pinsker, under the peak energy constraint, the best error exponent for communicating an M-ary message, M ≥ 3, with noise-free feedback is strictly larger than the one without feedback. This paper extends Pinsker´s result and shows that if the noise power in the feedback link is sufficiently small, the best error exponent for communicating an M-ary message can be strictly larger than the one without feedback. The proof involves two feedback coding schemes. One is motivated by a two-stage noisy feedback coding scheme of Burnashev and Yamamoto for binary symmetric channels, while the other is a linear noisy feedback coding scheme that extends Pinsker´s noise-free feedback coding scheme. When the feedback noise power α is sufficiently small, the linear coding scheme outperforms the two-stage (nonlinear) coding scheme, and is asymptotically optimal as α tends to zero. By contrast, when α is relatively larger, the two-stage coding scheme performs better.
  • Keywords
    Gaussian channels; encoding; M-ary message; Pinsker noise free feedback coding scheme; binary symmetric channels; error exponent; linear noisy feedback coding scheme; noise power; optimal coding; orthogonal additive white Gaussian noise channel; peak energy constraint; AWGN channels; Channel coding; Decoding; Noise; Noise measurement; Reliability; Error exponent; Gaussian channel; noisy feedback; peak energy constraint;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2013.2254233
  • Filename
    6508955