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
Link To Document