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System power consumption minimization for multichannel communications using cognitive radio

Authors: An He; Srikathyayani Srikanteswara; Kyung Kyoon Bae; Timothy R. Newman; Jeffrey H. Reed; William H. Tranter; Masoud Sajadieh; +1 Authors

System power consumption minimization for multichannel communications using cognitive radio

Abstract

Power consumption has been a significant issue for many mobile and wireless devices, especially those with high rate applications. This paper presents a methodology and framework to minimize system power consumption for multichannel communications using cognitive radio (CR) based on the application quality of service requirement, the channel condition, and the radio capabilities and characteristics. The CR framework enables an adaptation process that is aware of the radio (component) capabilities and characteristics. This paper mathematically formulates a system power consumption minimization problem under a rate constraint for multichannel communications and develops numerical solutions. Simulation results show that the knowledge of the radio capabilities and characteristics can help to reduce system power consumption significantly (e.g., up to 55% for a multichannel system with Class A power amplifiers).

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
14
Average
Top 10%
Average
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