DocumentCode
3131645
Title
Ergodic capacity ordering of fading channels
Author
Rajan, Adithya ; Tepedelenlioglu, Cihan
Author_Institution
Sch. of Electr., Comput. & Energy Eng., Arizona State Univ., Tempe, AZ, USA
fYear
2012
fDate
1-6 July 2012
Firstpage
870
Lastpage
874
Abstract
In this paper, a new stochastic order between two fading distributions is introduced. A fading channel dominates another in the capacity ordering sense, if the ergodic capacity of the first is greater than that of the second at all values of average signal to noise ratio. We show that many parametric fading models such as the Nakagami-m, Rician and Hoyt fading satisfy the capacity order, in the sense that the distribution with a larger line of sight parameter is larger in the ergodic capacity sense. Further, we obtain closure properties of the capacity order for the first time, because such a stochastic order has not been considered in either stochastic ordering literature, or information theory literature. Through these properties, we develop sufficient conditions for comparing the ergodic capacity of a composite system involving multiple capacity ordered fading links with coding/decoding capabilities only at the transmitter/receiver, when operated in two different fading scenarios. Such comparisons can be made even in cases when a closed form expression for the ergodic capacity of the composite system is not analytically tractable. We also show that capacity ordering of point-to-point links has applications to multiple access channels.
Keywords
channel capacity; decoding; fading channels; multi-access systems; radio receivers; radio transmitters; stochastic processes; Hoyt fading channel; Nakagami-m channel; Rician channel; average signal to noise ratio; coding-decoding capabilities; fading channel ergodic capacity ordering; fading distributions; fading links; information theory literature; multiple access channels; point-to-point links; stochastic ordering literature; Diversity reception; Fading; Laplace equations; Random variables; Relays; Signal to noise ratio; Stochastic processes;
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.2012.6284686
Filename
6284686
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