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The Capacity of Average and Peak Power Constrained Fading Channels with Channel Side Information

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dc.contributor.author Khojastepour, Mohammad
Aazhang, Behnaam
dc.creator Khojastepour, Mohammad
Aazhang, Behnaam
dc.date.accessioned 2007-10-31T00:49:50Z
dc.date.available 2007-10-31T00:49:50Z
dc.date.issued 2004-03-01
dc.date.submitted 2004-03-01
dc.identifier.uri http://hdl.handle.net/1911/20019
dc.description Conference Paper
dc.description.abstract We derive the ergodic capacity of discrete-time fading channel with additive Gaussian noise subject to both peak and average power constraint. The average power can be interpreted as the cost that we incur to achieve a certain rate. On the other hand, the motivation of this analysis comes from the fact that there is also a peak power limitation in practical communication system. It is been shown that the optimal power adaption is no longer water-filling or constant power adaption which is the case where there is no limitation on the peak power. The numerical results show that the importance of peak power constraint become negligible for relatively low available average power, while it is limiting the capacity to be finite even as available average power goes to infinity.
dc.language.iso eng
dc.subject capacity
fading channl
peak power
average power
dc.title The Capacity of Average and Peak Power Constrained Fading Channels with Channel Side Information
dc.type Conference Paper
dc.date.note 2004-05-17
dc.citation.bibtexName inproceedings
dc.date.modified 2004-05-17
dc.contributor.center Center for Multimedia Communications (http://cmc.rice.edu/)
dc.subject.keyword capacity
fading channl
peak power
average power
dc.citation.conferenceName IEEE Wireless Communications and Networking Conference
dc.type.dcmi Text
dc.identifier.citation M. Khojastepour and B. Aazhang,"The Capacity of Average and Peak Power Constrained Fading Channels with Channel Side Information," in IEEE Wireless Communications and Networking Conference,

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    Publications by Rice University Electrical and Computer Engineering faculty and graduate students