Performance Bounds for Detect and Avoid Signal Sensing

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dc.contributor.author Reisenfeld, Sam en_US
dc.contributor.editor NA en_US
dc.date.accessioned 2010-07-13T08:50:19Z
dc.date.available 2010-07-13T08:50:19Z
dc.date.issued 2009 en_US
dc.identifier 2009005823 en_US
dc.identifier.citation Reisenfeld Sam 2009, 'Performance Bounds for Detect and Avoid Signal Sensing', IEEE, Piscataway, USA, pp. 132-137. en_US
dc.identifier.issn 978-1-4244-4583-7 en_US
dc.identifier.other E1 en_US
dc.identifier.uri http://hdl.handle.net/10453/12647
dc.description.abstract Detect and Avoid (DAA) is a Cognitive Radio technique for a primary user and secondary users sharing the same spectrum. The DAA spectral sensing system must provide both low decision delay and highly reliable decisions on the presence/absence of primary user transmission. These results provide upper and lower bounds on the decision error rate performance of sensing systems as a function of SNR (signal-tonoise ratio) and the number of samples used in the sensing decision. The bounds represent benchmarks on the performances of practical detection systems and give insight into the trade-off between sensing performance and decision delay. en_US
dc.language en_US
dc.publisher IEEE en_US
dc.relation.isbasedon NA en_US
dc.title Performance Bounds for Detect and Avoid Signal Sensing en_US
dc.parent Proceedings of CogArt2009 en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation Piscataway, USA en_US
dc.identifier.startpage 132 en_US
dc.identifier.endpage 137 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.for 080500 en_US
dc.personcode 880567 en_US
dc.percentage 100 en_US
dc.classification.name Distributed Computing en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom International Conference on Cognitive Radio and Advanced Spectrum Management en_US
dc.date.activity 20090518 en_US
dc.location.activity Aalborg, Denmark en_US
dc.description.keywords NA en_US
dc.staffid en_US
dc.staffid 880567 en_US


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