Energy Detection Based Spectrum Sensing for Cognitive Radios in Noise of Uncertain Power
Energy detection based spectrum sensing has been proposed and studied widely for primary user (PU) signal detection in the literature. With the help of multiple secondary users (SU) in the cognitive radio network, various cooperative sensing schemes are investigated to enhance the energy detection p...
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creator | Shent, B. Longyang Huang Chengshi Zhao Zheng Zhou Kyungsup Kwak |
description | Energy detection based spectrum sensing has been proposed and studied widely for primary user (PU) signal detection in the literature. With the help of multiple secondary users (SU) in the cognitive radio network, various cooperative sensing schemes are investigated to enhance the energy detection performance. However, the impacts of noise power fluctuating effects on the detection performance in multipath fading and user cooperative sensing scenarios are seldom evaluated in relevant literature. In this paper, a modified version of the classic energy detection model is presented, where the noise power uncertainty (U) is introduced into threshold setting. With a reasonable approximate derivation, we provide accurate predictions of SNRwall constraints imposed by U in Rayleigh fading environments. In addition, by employing a simple hard decision fusion rule, the collaborative gain in spectrum sensing performance is also quantified with respect to U. Our analysis and numerical results confirm that collaboration can significantly improve the spectrum sensing performance in a noise power fluctuating environment. |
doi_str_mv | 10.1109/ISCIT.2008.4700269 |
format | Conference Proceeding |
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With the help of multiple secondary users (SU) in the cognitive radio network, various cooperative sensing schemes are investigated to enhance the energy detection performance. However, the impacts of noise power fluctuating effects on the detection performance in multipath fading and user cooperative sensing scenarios are seldom evaluated in relevant literature. In this paper, a modified version of the classic energy detection model is presented, where the noise power uncertainty (U) is introduced into threshold setting. With a reasonable approximate derivation, we provide accurate predictions of SNRwall constraints imposed by U in Rayleigh fading environments. In addition, by employing a simple hard decision fusion rule, the collaborative gain in spectrum sensing performance is also quantified with respect to U. 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With the help of multiple secondary users (SU) in the cognitive radio network, various cooperative sensing schemes are investigated to enhance the energy detection performance. However, the impacts of noise power fluctuating effects on the detection performance in multipath fading and user cooperative sensing scenarios are seldom evaluated in relevant literature. In this paper, a modified version of the classic energy detection model is presented, where the noise power uncertainty (U) is introduced into threshold setting. With a reasonable approximate derivation, we provide accurate predictions of SNRwall constraints imposed by U in Rayleigh fading environments. In addition, by employing a simple hard decision fusion rule, the collaborative gain in spectrum sensing performance is also quantified with respect to U. Our analysis and numerical results confirm that collaboration can significantly improve the spectrum sensing performance in a noise power fluctuating environment.</description><subject>Background noise</subject><subject>Cognitive radio</subject><subject>Collaboration</subject><subject>Detectors</subject><subject>Estimation error</subject><subject>Fading</subject><subject>Interference</subject><subject>Signal detection</subject><subject>Uncertainty</subject><subject>Working environment noise</subject><isbn>9781424423354</isbn><isbn>142442335X</isbn><isbn>1424423368</isbn><isbn>9781424423361</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2008</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1kM1KAzEcxCNS0Na-gF7yAq35_jjqWrVQVGwL3kq6-88SsUlJVqVv74p1LsNvGOYwCF1SMqWU2Ov5spqvpowQMxWaEKbsCRpSwYRgnCtzisZWm3-WYoCGv11LmJH0DI1LeSe9hORc6HP0NouQ2wO-gw7qLqSIb12BBi_3PebPHV5CLCG22KeMq9TG0IUvwK-uCangEPFTCgVw8ngda8id66OX9A35Ag28-ygwPvoIre9nq-pxsnh-mFc3i0mgUnUT75TiAojisra1N-CsdEwZ0YBqqLbU2EZtieVaC76VXErDfeOY4KCls56P0NXfbgCAzT6HncuHzfEZ_gPBS1SQ</recordid><startdate>200810</startdate><enddate>200810</enddate><creator>Shent, B.</creator><creator>Longyang Huang</creator><creator>Chengshi Zhao</creator><creator>Zheng Zhou</creator><creator>Kyungsup Kwak</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200810</creationdate><title>Energy Detection Based Spectrum Sensing for Cognitive Radios in Noise of Uncertain Power</title><author>Shent, B. ; Longyang Huang ; Chengshi Zhao ; Zheng Zhou ; Kyungsup Kwak</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i156t-fa6634e0635c9cf8ea95a2684de6d179189d6b0937743b535583fda243e75a9f3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng ; jpn</language><creationdate>2008</creationdate><topic>Background noise</topic><topic>Cognitive radio</topic><topic>Collaboration</topic><topic>Detectors</topic><topic>Estimation error</topic><topic>Fading</topic><topic>Interference</topic><topic>Signal detection</topic><topic>Uncertainty</topic><topic>Working environment noise</topic><toplevel>online_resources</toplevel><creatorcontrib>Shent, B.</creatorcontrib><creatorcontrib>Longyang Huang</creatorcontrib><creatorcontrib>Chengshi Zhao</creatorcontrib><creatorcontrib>Zheng Zhou</creatorcontrib><creatorcontrib>Kyungsup Kwak</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Shent, B.</au><au>Longyang Huang</au><au>Chengshi Zhao</au><au>Zheng Zhou</au><au>Kyungsup Kwak</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Energy Detection Based Spectrum Sensing for Cognitive Radios in Noise of Uncertain Power</atitle><btitle>2008 International Symposium on Communications and Information Technologies</btitle><stitle>ISCIT</stitle><date>2008-10</date><risdate>2008</risdate><spage>628</spage><epage>633</epage><pages>628-633</pages><isbn>9781424423354</isbn><isbn>142442335X</isbn><eisbn>1424423368</eisbn><eisbn>9781424423361</eisbn><abstract>Energy detection based spectrum sensing has been proposed and studied widely for primary user (PU) signal detection in the literature. With the help of multiple secondary users (SU) in the cognitive radio network, various cooperative sensing schemes are investigated to enhance the energy detection performance. However, the impacts of noise power fluctuating effects on the detection performance in multipath fading and user cooperative sensing scenarios are seldom evaluated in relevant literature. In this paper, a modified version of the classic energy detection model is presented, where the noise power uncertainty (U) is introduced into threshold setting. With a reasonable approximate derivation, we provide accurate predictions of SNRwall constraints imposed by U in Rayleigh fading environments. In addition, by employing a simple hard decision fusion rule, the collaborative gain in spectrum sensing performance is also quantified with respect to U. Our analysis and numerical results confirm that collaboration can significantly improve the spectrum sensing performance in a noise power fluctuating environment.</abstract><pub>IEEE</pub><doi>10.1109/ISCIT.2008.4700269</doi><tpages>6</tpages></addata></record> |
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language | eng ; jpn |
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source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Background noise Cognitive radio Collaboration Detectors Estimation error Fading Interference Signal detection Uncertainty Working environment noise |
title | Energy Detection Based Spectrum Sensing for Cognitive Radios in Noise of Uncertain Power |
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