Adaptive Bistable Stochastic Resonance Aided Spectrum Sensing
As a fundamental technology of cognitive radio, the spectrum sensing scheme is required to perform well in low signal-to-noise ratio (SNR) environments. In this paper, we propose a novel spectrum sensing method based on adaptive bistable stochastic resonance (A-BSR). By maximizing the SNR gain intro...
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| Veröffentlicht in: | IEEE transactions on wireless communications 2014-07, Vol.13 (7), p.4014-4024 |
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| creator | Wang, Jun Ren, Xin Zhang, Shaowen Zhang, Daiming Li, Husheng Li, Shaoqian |
| description | As a fundamental technology of cognitive radio, the spectrum sensing scheme is required to perform well in low signal-to-noise ratio (SNR) environments. In this paper, we propose a novel spectrum sensing method based on adaptive bistable stochastic resonance (A-BSR). By maximizing the SNR gain introduced by the BSR system, we first present an A-BSR system, of which the parameters can be adaptively adjusted based on the background noise. Then, we propose an A-BSR aided spectrum sensing scheme by passing the received signal through an A-BSR system to improve SNR. Based on the characteristics of A-BSR system output in frequency and time domains, we further propose two energy detection (ED)-based spectrum sensing algorithms. As the output of an A-BSR system given a noise input is concentrated around frequency zero, we propose a modified ED based on periodogram (P-ED) in frequency domain. Moreover, as the A-BSR system output for noise input has approximate constant amplitude in time domain, a novel deviation-based ED (D-ED) is proposed. Extensive simulation results show that the proposed A-BSR aided spectrum sensing scheme can achieve much better performance than the existing ED and BSR aided spectrum sensing schemes with fixed parameters, especially under very low SNR region. |
| doi_str_mv | 10.1109/TWC.2014.2317779 |
| format | Article |
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In this paper, we propose a novel spectrum sensing method based on adaptive bistable stochastic resonance (A-BSR). By maximizing the SNR gain introduced by the BSR system, we first present an A-BSR system, of which the parameters can be adaptively adjusted based on the background noise. Then, we propose an A-BSR aided spectrum sensing scheme by passing the received signal through an A-BSR system to improve SNR. Based on the characteristics of A-BSR system output in frequency and time domains, we further propose two energy detection (ED)-based spectrum sensing algorithms. As the output of an A-BSR system given a noise input is concentrated around frequency zero, we propose a modified ED based on periodogram (P-ED) in frequency domain. Moreover, as the A-BSR system output for noise input has approximate constant amplitude in time domain, a novel deviation-based ED (D-ED) is proposed. Extensive simulation results show that the proposed A-BSR aided spectrum sensing scheme can achieve much better performance than the existing ED and BSR aided spectrum sensing schemes with fixed parameters, especially under very low SNR region.</description><identifier>ISSN: 1536-1276</identifier><identifier>EISSN: 1558-2248</identifier><identifier>DOI: 10.1109/TWC.2014.2317779</identifier><identifier>CODEN: ITWCAX</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Adaptive systems ; Algorithms ; Applied sciences ; Approximation ; Cognitive radio ; Constants ; Detection ; Exact sciences and technology ; Frequency-domain analysis ; Information, signal and communications theory ; Noise ; Radiocommunication specific techniques ; Radiocommunications ; Sensors ; Signal and communications theory ; Signal representation. Spectral analysis ; Signal to noise ratio ; Signal, noise ; Stochastic resonance ; Telecommunications ; Telecommunications and information theory ; Time domain ; Wireless communication</subject><ispartof>IEEE transactions on wireless communications, 2014-07, Vol.13 (7), p.4014-4024</ispartof><rights>2015 INIST-CNRS</rights><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Jul 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c420t-242ad32d4c42c95ccbdb33f3737806b5d2391c4b6819aafc71aea9c53826aafe3</citedby><cites>FETCH-LOGICAL-c420t-242ad32d4c42c95ccbdb33f3737806b5d2391c4b6819aafc71aea9c53826aafe3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6800106$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6800106$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28721518$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Wang, Jun</creatorcontrib><creatorcontrib>Ren, Xin</creatorcontrib><creatorcontrib>Zhang, Shaowen</creatorcontrib><creatorcontrib>Zhang, Daiming</creatorcontrib><creatorcontrib>Li, Husheng</creatorcontrib><creatorcontrib>Li, Shaoqian</creatorcontrib><title>Adaptive Bistable Stochastic Resonance Aided Spectrum Sensing</title><title>IEEE transactions on wireless communications</title><addtitle>TWC</addtitle><description>As a fundamental technology of cognitive radio, the spectrum sensing scheme is required to perform well in low signal-to-noise ratio (SNR) environments. In this paper, we propose a novel spectrum sensing method based on adaptive bistable stochastic resonance (A-BSR). By maximizing the SNR gain introduced by the BSR system, we first present an A-BSR system, of which the parameters can be adaptively adjusted based on the background noise. Then, we propose an A-BSR aided spectrum sensing scheme by passing the received signal through an A-BSR system to improve SNR. Based on the characteristics of A-BSR system output in frequency and time domains, we further propose two energy detection (ED)-based spectrum sensing algorithms. As the output of an A-BSR system given a noise input is concentrated around frequency zero, we propose a modified ED based on periodogram (P-ED) in frequency domain. Moreover, as the A-BSR system output for noise input has approximate constant amplitude in time domain, a novel deviation-based ED (D-ED) is proposed. Extensive simulation results show that the proposed A-BSR aided spectrum sensing scheme can achieve much better performance than the existing ED and BSR aided spectrum sensing schemes with fixed parameters, especially under very low SNR region.</description><subject>Adaptive systems</subject><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Approximation</subject><subject>Cognitive radio</subject><subject>Constants</subject><subject>Detection</subject><subject>Exact sciences and technology</subject><subject>Frequency-domain analysis</subject><subject>Information, signal and communications theory</subject><subject>Noise</subject><subject>Radiocommunication specific techniques</subject><subject>Radiocommunications</subject><subject>Sensors</subject><subject>Signal and communications theory</subject><subject>Signal representation. Spectral analysis</subject><subject>Signal to noise ratio</subject><subject>Signal, noise</subject><subject>Stochastic resonance</subject><subject>Telecommunications</subject><subject>Telecommunications and information theory</subject><subject>Time domain</subject><subject>Wireless communication</subject><issn>1536-1276</issn><issn>1558-2248</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkEtLw0AQgIMoWKt3wUtABC-p-34cPNTiCwqCrXhcNpuJbkmTupsI_nu3tHjwNDPMN8PMl2XnGE0wRvpm-T6bEITZhFAspdQH2QhzrgpCmDrc5lQUmEhxnJ3EuEIIS8H5KLudVnbT-2_I73zsbdlAvug792lj713-CrFrbesgn_oKqnyxAdeHYZ0voI2-_TjNjmrbRDjbx3H29nC_nD0V85fH59l0XjhGUF8QRmxFScVS6TR3rqxKSmsqqVRIlLwiVGPHSqGwtrZ2Eluw2nGqiEg10HF2vdu7Cd3XALE3ax8dNI1toRuiSZ9qoZmUPKGX_9BVN4Q2XZcoJjBjjMtEoR3lQhdjgNpsgl_b8GMwMlufJvk0W59m7zONXO0X2-hsU4fkxce_OaIkwRyrxF3sOA8Af22hknIk6C9YVnzA</recordid><startdate>20140701</startdate><enddate>20140701</enddate><creator>Wang, Jun</creator><creator>Ren, Xin</creator><creator>Zhang, Shaowen</creator><creator>Zhang, Daiming</creator><creator>Li, Husheng</creator><creator>Li, Shaoqian</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Spectral analysis</topic><topic>Signal to noise ratio</topic><topic>Signal, noise</topic><topic>Stochastic resonance</topic><topic>Telecommunications</topic><topic>Telecommunications and information theory</topic><topic>Time domain</topic><topic>Wireless communication</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Jun</creatorcontrib><creatorcontrib>Ren, Xin</creatorcontrib><creatorcontrib>Zhang, Shaowen</creatorcontrib><creatorcontrib>Zhang, Daiming</creatorcontrib><creatorcontrib>Li, Husheng</creatorcontrib><creatorcontrib>Li, Shaoqian</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>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><jtitle>IEEE transactions on wireless communications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Wang, Jun</au><au>Ren, Xin</au><au>Zhang, Shaowen</au><au>Zhang, Daiming</au><au>Li, Husheng</au><au>Li, Shaoqian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Adaptive Bistable Stochastic Resonance Aided Spectrum Sensing</atitle><jtitle>IEEE transactions on wireless communications</jtitle><stitle>TWC</stitle><date>2014-07-01</date><risdate>2014</risdate><volume>13</volume><issue>7</issue><spage>4014</spage><epage>4024</epage><pages>4014-4024</pages><issn>1536-1276</issn><eissn>1558-2248</eissn><coden>ITWCAX</coden><abstract>As a fundamental technology of cognitive radio, the spectrum sensing scheme is required to perform well in low signal-to-noise ratio (SNR) environments. In this paper, we propose a novel spectrum sensing method based on adaptive bistable stochastic resonance (A-BSR). By maximizing the SNR gain introduced by the BSR system, we first present an A-BSR system, of which the parameters can be adaptively adjusted based on the background noise. Then, we propose an A-BSR aided spectrum sensing scheme by passing the received signal through an A-BSR system to improve SNR. Based on the characteristics of A-BSR system output in frequency and time domains, we further propose two energy detection (ED)-based spectrum sensing algorithms. As the output of an A-BSR system given a noise input is concentrated around frequency zero, we propose a modified ED based on periodogram (P-ED) in frequency domain. Moreover, as the A-BSR system output for noise input has approximate constant amplitude in time domain, a novel deviation-based ED (D-ED) is proposed. Extensive simulation results show that the proposed A-BSR aided spectrum sensing scheme can achieve much better performance than the existing ED and BSR aided spectrum sensing schemes with fixed parameters, especially under very low SNR region.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/TWC.2014.2317779</doi><tpages>11</tpages></addata></record> |
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| subjects | Adaptive systems Algorithms Applied sciences Approximation Cognitive radio Constants Detection Exact sciences and technology Frequency-domain analysis Information, signal and communications theory Noise Radiocommunication specific techniques Radiocommunications Sensors Signal and communications theory Signal representation. Spectral analysis Signal to noise ratio Signal, noise Stochastic resonance Telecommunications Telecommunications and information theory Time domain Wireless communication |
| title | Adaptive Bistable Stochastic Resonance Aided Spectrum Sensing |
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