• DocumentCode
    1014187
  • Title

    Capacity of nearly decomposable Markovian fading channels under asymmetric receiver-sender side information

  • Author

    Médard, Muriel ; Srikant, R.

  • Author_Institution
    Lab. for Inf. & Decision Syst., MIT, Cambridge, MA, USA
  • Volume
    52
  • Issue
    7
  • fYear
    2006
  • fDate
    7/1/2006 12:00:00 AM
  • Firstpage
    3052
  • Lastpage
    3062
  • Abstract
    We investigate the following issue: if fast fades are Markovian and known at the receiver, while the transmitter has only a coarse quantization of the fading process, what capacity penalty comes from having the transmitter act on the current coarse quantization alone? For time-varying channels which experience rapid time variations, sender and receiver typically have asymmetric channel side information. To avoid the expense of providing, through feedback, detailed channel side information to the sender, the receiver offers the sender only a coarse, generally time-averaged, representation of the state of the channel, which we term slow variations. Thus, the receiver tracks the fast variations of the channel (and the slow ones perforce) while the sender receives feedback only about the slow variations. While the fast variations (micro-states) remain Markovian, the slow variations (macro-states) are not. We compute an approximate channel capacity in the following sense: each rate smaller than the "approximate" capacity, computed using results by Caire and Shamai, can be achieved for sufficiently large separation between the time scales for the slow and fast fades. The difference between the true capacity and the approximate capacity is O(εlog2(ε)log(-log(ε))), where ε is the ratio between the speed of variation of the channel in the macro- and micro-states. The approximate capacity is computed by power allocation between the slowly varying states using appropriate water filling.
  • Keywords
    approximation theory; channel capacity; fading channels; quantisation (signal); time-varying channels; Markovian process; approximation; channel capacity; coarse quantization; fading channel; feedback; power allocation; receiver; receiver-sender side information; time-varying channel; transmitter; water filling; Channel capacity; Engineering profession; Fading; Filling; History; Information theory; Quantization; State feedback; Time-varying channels; Transmitters; Capacity; Markovian models; channel side information;
  • fLanguage
    English
  • Journal_Title
    Information Theory, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9448
  • Type

    jour

  • DOI
    10.1109/TIT.2006.872843
  • Filename
    1650355