What is a Spectrum Hole and What Does it Take to Recognize One?

ldquoSpectrum holesrdquo represent the potential opportunities for noninterfering (safe) use of spectrum and can be considered as multidimensional regions within frequency, time, and space. The main challenge for secondary radio systems is to be able to robustly sense when they are within such a spe...

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Veröffentlicht in:Proceedings of the IEEE 2009-05, Vol.97 (5), p.824-848
Hauptverfasser: Tandra, Rahul, Mishra, Shridhar Mubaraq, Sahai, Anant
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container_end_page 848
container_issue 5
container_start_page 824
container_title Proceedings of the IEEE
container_volume 97
creator Tandra, Rahul
Mishra, Shridhar Mubaraq
Sahai, Anant
description ldquoSpectrum holesrdquo represent the potential opportunities for noninterfering (safe) use of spectrum and can be considered as multidimensional regions within frequency, time, and space. The main challenge for secondary radio systems is to be able to robustly sense when they are within such a spectrum hole. To allow a unified discussion of the core issues in spectrum sensing, the ldquoweighted probability of area recoveredrdquo (WPAR) metric is introduced to measure the performance of a sensing strategy; and the ldquofear of harmful interferencerdquo F HI metric is introduced to measure its safety. These metrics explicitly consider the impact of asymmetric uncertainties (and misaligned incentives) in the system model. Furthermore, they allow a meaningful comparison of diverse approaches to spectrum sensing unlike the traditional triad of sensitivity, probability of false-alarm P FA , and probability of missed-detection P MD . These new metrics are used to show that fading uncertainty forces the WPAR performance of single-radio sensing algorithms to be very low for small values of F HI , even for ideal detectors. Cooperative sensing algorithms enable a much higher WPAR, but only if users are guaranteed to experience independent fading. Lastly, in-the-field calibration for wide-band (but uncertain) environment variables (e.g., interference and shadowing) can robustly guarantee safety (low F HI ) even in the face of potentially correlated users without sacrificing WPAR.
doi_str_mv 10.1109/JPROC.2009.2015710
format Article
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The main challenge for secondary radio systems is to be able to robustly sense when they are within such a spectrum hole. To allow a unified discussion of the core issues in spectrum sensing, the ldquoweighted probability of area recoveredrdquo (WPAR) metric is introduced to measure the performance of a sensing strategy; and the ldquofear of harmful interferencerdquo F HI metric is introduced to measure its safety. These metrics explicitly consider the impact of asymmetric uncertainties (and misaligned incentives) in the system model. Furthermore, they allow a meaningful comparison of diverse approaches to spectrum sensing unlike the traditional triad of sensitivity, probability of false-alarm P FA , and probability of missed-detection P MD . These new metrics are used to show that fading uncertainty forces the WPAR performance of single-radio sensing algorithms to be very low for small values of F HI , even for ideal detectors. Cooperative sensing algorithms enable a much higher WPAR, but only if users are guaranteed to experience independent fading. Lastly, in-the-field calibration for wide-band (but uncertain) environment variables (e.g., interference and shadowing) can robustly guarantee safety (low F HI ) even in the face of potentially correlated users without sacrificing WPAR.</description><identifier>ISSN: 0018-9219</identifier><identifier>EISSN: 1558-2256</identifier><identifier>DOI: 10.1109/JPROC.2009.2015710</identifier><identifier>CODEN: IEEPAD</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Area measurement ; Assisted detection ; Calibration ; cognitive radio ; cooperation ; Detection ; Detectors ; dynamic spectrum ; Fading ; Frequency ; Interference ; Mathematical models ; Multidimensional systems ; robust sensing metrics ; Robustness ; Safety ; spectrum holes ; spectrum sensing ; Strategy ; Uncertainty</subject><ispartof>Proceedings of the IEEE, 2009-05, Vol.97 (5), p.824-848</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2009</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c390t-199abe051ab64dfdeaf13bc9374006b6512e3cfd12916080674167f668b2de133</citedby><cites>FETCH-LOGICAL-c390t-199abe051ab64dfdeaf13bc9374006b6512e3cfd12916080674167f668b2de133</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4895279$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4895279$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Tandra, Rahul</creatorcontrib><creatorcontrib>Mishra, Shridhar Mubaraq</creatorcontrib><creatorcontrib>Sahai, Anant</creatorcontrib><title>What is a Spectrum Hole and What Does it Take to Recognize One?</title><title>Proceedings of the IEEE</title><addtitle>JPROC</addtitle><description>ldquoSpectrum holesrdquo represent the potential opportunities for noninterfering (safe) use of spectrum and can be considered as multidimensional regions within frequency, time, and space. The main challenge for secondary radio systems is to be able to robustly sense when they are within such a spectrum hole. To allow a unified discussion of the core issues in spectrum sensing, the ldquoweighted probability of area recoveredrdquo (WPAR) metric is introduced to measure the performance of a sensing strategy; and the ldquofear of harmful interferencerdquo F HI metric is introduced to measure its safety. These metrics explicitly consider the impact of asymmetric uncertainties (and misaligned incentives) in the system model. Furthermore, they allow a meaningful comparison of diverse approaches to spectrum sensing unlike the traditional triad of sensitivity, probability of false-alarm P FA , and probability of missed-detection P MD . These new metrics are used to show that fading uncertainty forces the WPAR performance of single-radio sensing algorithms to be very low for small values of F HI , even for ideal detectors. Cooperative sensing algorithms enable a much higher WPAR, but only if users are guaranteed to experience independent fading. Lastly, in-the-field calibration for wide-band (but uncertain) environment variables (e.g., interference and shadowing) can robustly guarantee safety (low F HI ) even in the face of potentially correlated users without sacrificing WPAR.</description><subject>Algorithms</subject><subject>Area measurement</subject><subject>Assisted detection</subject><subject>Calibration</subject><subject>cognitive radio</subject><subject>cooperation</subject><subject>Detection</subject><subject>Detectors</subject><subject>dynamic spectrum</subject><subject>Fading</subject><subject>Frequency</subject><subject>Interference</subject><subject>Mathematical models</subject><subject>Multidimensional systems</subject><subject>robust sensing metrics</subject><subject>Robustness</subject><subject>Safety</subject><subject>spectrum holes</subject><subject>spectrum sensing</subject><subject>Strategy</subject><subject>Uncertainty</subject><issn>0018-9219</issn><issn>1558-2256</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2009</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNp9kT1Pw0AMhk8IJErhD8ByYgCWgH2X-5oqVD4KqlTEhxijS-JAoE1KLh3g15NSxMDQxR78vJath7F9hFNEcGe3d_eT4akAcF1BZRA2WA-VspEQSm-yHgDayAl022wnhDcAkErLHhs8v_qWl4F7_jCnrG0WMz6qp8R9lfOf2UVNgZctf_TvxNua31NWv1TlF_FJRYNdtlX4aaC9395nT1eXj8NRNJ5c3wzPx1EmHbQROudTAoU-1XFe5OQLlGnmpIkBdKoVCpJZkaNwqMGCNjFqU2htU5ETStlnx6u986b-WFBok1kZMppOfUX1IiTWKJAu1tiRR2tJGRs0SpsOPFkLIojuGoztEj38h77Vi6bqHk6sslaBc9BBYgVlTR1CQ0Uyb8qZbz67TcnSUvJjKVlaSn4tdaGDVagkor9AbJ0SxslvznSJ3Q</recordid><startdate>20090501</startdate><enddate>20090501</enddate><creator>Tandra, Rahul</creator><creator>Mishra, Shridhar Mubaraq</creator><creator>Sahai, Anant</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SP</scope><scope>8FD</scope><scope>L7M</scope><scope>F28</scope><scope>FR3</scope></search><sort><creationdate>20090501</creationdate><title>What is a Spectrum Hole and What Does it Take to Recognize One?</title><author>Tandra, Rahul ; Mishra, Shridhar Mubaraq ; Sahai, Anant</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c390t-199abe051ab64dfdeaf13bc9374006b6512e3cfd12916080674167f668b2de133</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Algorithms</topic><topic>Area measurement</topic><topic>Assisted detection</topic><topic>Calibration</topic><topic>cognitive radio</topic><topic>cooperation</topic><topic>Detection</topic><topic>Detectors</topic><topic>dynamic spectrum</topic><topic>Fading</topic><topic>Frequency</topic><topic>Interference</topic><topic>Mathematical models</topic><topic>Multidimensional systems</topic><topic>robust sensing metrics</topic><topic>Robustness</topic><topic>Safety</topic><topic>spectrum holes</topic><topic>spectrum sensing</topic><topic>Strategy</topic><topic>Uncertainty</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tandra, Rahul</creatorcontrib><creatorcontrib>Mishra, Shridhar Mubaraq</creatorcontrib><creatorcontrib>Sahai, Anant</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Technology Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>ANTE: Abstracts in New Technology &amp; Engineering</collection><collection>Engineering Research Database</collection><jtitle>Proceedings of the IEEE</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Tandra, Rahul</au><au>Mishra, Shridhar Mubaraq</au><au>Sahai, Anant</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>What is a Spectrum Hole and What Does it Take to Recognize One?</atitle><jtitle>Proceedings of the IEEE</jtitle><stitle>JPROC</stitle><date>2009-05-01</date><risdate>2009</risdate><volume>97</volume><issue>5</issue><spage>824</spage><epage>848</epage><pages>824-848</pages><issn>0018-9219</issn><eissn>1558-2256</eissn><coden>IEEPAD</coden><abstract>ldquoSpectrum holesrdquo represent the potential opportunities for noninterfering (safe) use of spectrum and can be considered as multidimensional regions within frequency, time, and space. The main challenge for secondary radio systems is to be able to robustly sense when they are within such a spectrum hole. To allow a unified discussion of the core issues in spectrum sensing, the ldquoweighted probability of area recoveredrdquo (WPAR) metric is introduced to measure the performance of a sensing strategy; and the ldquofear of harmful interferencerdquo F HI metric is introduced to measure its safety. These metrics explicitly consider the impact of asymmetric uncertainties (and misaligned incentives) in the system model. Furthermore, they allow a meaningful comparison of diverse approaches to spectrum sensing unlike the traditional triad of sensitivity, probability of false-alarm P FA , and probability of missed-detection P MD . These new metrics are used to show that fading uncertainty forces the WPAR performance of single-radio sensing algorithms to be very low for small values of F HI , even for ideal detectors. Cooperative sensing algorithms enable a much higher WPAR, but only if users are guaranteed to experience independent fading. Lastly, in-the-field calibration for wide-band (but uncertain) environment variables (e.g., interference and shadowing) can robustly guarantee safety (low F HI ) even in the face of potentially correlated users without sacrificing WPAR.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/JPROC.2009.2015710</doi><tpages>25</tpages></addata></record>
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ispartof Proceedings of the IEEE, 2009-05, Vol.97 (5), p.824-848
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source IEEE Electronic Library (IEL)
subjects Algorithms
Area measurement
Assisted detection
Calibration
cognitive radio
cooperation
Detection
Detectors
dynamic spectrum
Fading
Frequency
Interference
Mathematical models
Multidimensional systems
robust sensing metrics
Robustness
Safety
spectrum holes
spectrum sensing
Strategy
Uncertainty
title What is a Spectrum Hole and What Does it Take to Recognize One?
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