Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Conferences, Workshops, Symposiums, and Seminars
  4. On the use of training sequences for channel estimation
 
conference paper

On the use of training sequences for channel estimation

Tchamkerten, A  
•
Telatar, E  
2005
International Symposium on Information Theory 2005
International Symposium on Information Theory 2005

Suppose Q is a family of discrete memoryless channels. An unknown member of Q is available with perfect (causal) feedback for communication. A recent result (A. Tchamkerten and I.E. Telatar) shows the existence, for certain families of channels (e.g. binary symmetric channels and Z channels), of coding schemes that achieve Burnashev's exponent universally over these families. In other words, in certain cases, there is no loss in the error exponent by ignoring the channel: transmitter and receiver can design optimal blind coding schemes that perform as well as the best feedback coding schemes tuned for the channel under use. Here we study the situation where communication is carried by first testing the channel by means of a training sequence, then coding the information according to the channel estimate. We provide an upper bound on the maximum achievable error exponent of any such scheme. If we consider binary symmetric channels and Z channels this bound is much lower than Burnashev's exponent. This suggests that in terms of error exponent, a good universal feedback scheme entangles channel estimation with information delivery, rather than separating them.

  • Files
  • Details
  • Metrics
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés