• DocumentCode
    3125663
  • Title

    Amplification of the hidden Gaussian channel states

  • Author

    Tian, Chao

  • Author_Institution
    AT&T Labs.-Res., Florham Park, NJ, USA
  • fYear
    2012
  • fDate
    1-6 July 2012
  • Firstpage
    3068
  • Lastpage
    3072
  • Abstract
    We consider the problem of amplifying the channel states in a state-dependent Gaussian channel, where the encoder knows (non-causally) a noisy version of the channel states, i.e., the channel states are hidden under the noise. We provide a complete characterization of the minimum state reconstruction distortion at the decoder under a power constraint at the encoder, and show that a simple analog scheme with power control is optimal. More precisely, if the power available to the encoder is below certain threshold, the analog scheme using full power is optimal, however when the power available to the encoder is above that threshold, analog transmission using only a fixed amount of the available power is optimal. This is in contrast to the state amplification problem considered by Sutivong et al., when the channel states are known perfectly at the encoder for which the full power is always used in the optimal scheme. The converse proof of our result relies on a channel decomposition argument which was not necessary for the simpler case when the channel states are known perfectly.
  • Keywords
    Gaussian channels; channel coding; decoding; power control; analog transmission; channel decomposition argument; decoder; encoder; hidden Gaussian channel state amplification problem; minimum state reconstruction distortion; optimal power control; power constraint; simple analog scheme; state-dependent Gaussian channel; Decoding; Distortion measurement; Noise; Noise measurement; Power control; Silicon;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory Proceedings (ISIT), 2012 IEEE International Symposium on
  • Conference_Location
    Cambridge, MA
  • ISSN
    2157-8095
  • Print_ISBN
    978-1-4673-2580-6
  • Electronic_ISBN
    2157-8095
  • Type

    conf

  • DOI
    10.1109/ISIT.2012.6284126
  • Filename
    6284126