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Tunnelized Cyclostationary Signal Processing: A Novel Approach to Low-Energy Spectrum Sensing
We present novel tunnelized second- and higher-order cyclostationary signal processing algorithms to simultaneously detect and characterize RF signals. Techniques that exploit second- and higher-order cyclostationary features to detect and classify signals possess many desirable properties. However,...
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creator | Spooner, Chad M. Mody, Apurva N. Chuang, Jack Anthony, Michael P. |
description | We present novel tunnelized second- and higher-order cyclostationary signal processing algorithms to simultaneously detect and characterize RF signals. Techniques that exploit second- and higher-order cyclostationary features to detect and classify signals possess many desirable properties. However, their pervasive use and hardware implementation have been hampered because such features are highly complex, and consume substantial processor energy. In this paper we present a novel concept, where we observe that severe but purposeful under-sampling of the signals through tunneling preserves sufficient exploitable cyclostationarity, even when the tunnel bandwidth is much smaller than the signal bandwidth. This phenomenon is then exploited to create a low complexity and flexible suite of algorithms to simultaneously detect and characterize signals using their tunneling-distorted cyclostationary features. We also demonstrate that such algorithms can detect and characterize signals for a highly adverse signal-to-interference-plus-noise ratio, even when multiple signals completely overlap in time and frequency. |
doi_str_mv | 10.1109/MILCOM.2013.143 |
format | conference_proceeding |
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Techniques that exploit second- and higher-order cyclostationary features to detect and classify signals possess many desirable properties. However, their pervasive use and hardware implementation have been hampered because such features are highly complex, and consume substantial processor energy. In this paper we present a novel concept, where we observe that severe but purposeful under-sampling of the signals through tunneling preserves sufficient exploitable cyclostationarity, even when the tunnel bandwidth is much smaller than the signal bandwidth. This phenomenon is then exploited to create a low complexity and flexible suite of algorithms to simultaneously detect and characterize signals using their tunneling-distorted cyclostationary features. We also demonstrate that such algorithms can detect and characterize signals for a highly adverse signal-to-interference-plus-noise ratio, even when multiple signals completely overlap in time and frequency.</description><identifier>ISSN: 2155-7578</identifier><identifier>EISSN: 2155-7586</identifier><identifier>EISBN: 9780769551241</identifier><identifier>EISBN: 0769551246</identifier><identifier>DOI: 10.1109/MILCOM.2013.143</identifier><identifier>CODEN: IEEPAD</identifier><language>eng</language><publisher>IEEE</publisher><subject>Bandwidth ; cognitive radio ; energy detection ; higher-order cyclic cumulants ; Multiaccess communication ; Noise ; second-order cyclostationary processing ; Sensors ; Signal processing algorithms ; Spectrum sensing ; Spread spectrum communication ; Tunneling</subject><ispartof>MILCOM 2013 - 2013 IEEE Military Communications Conference, 2013, p.811-816</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6735724$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,27925,54555,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6735724$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Spooner, Chad M.</creatorcontrib><creatorcontrib>Mody, Apurva N.</creatorcontrib><creatorcontrib>Chuang, Jack</creatorcontrib><creatorcontrib>Anthony, Michael P.</creatorcontrib><title>Tunnelized Cyclostationary Signal Processing: A Novel Approach to Low-Energy Spectrum Sensing</title><title>MILCOM 2013 - 2013 IEEE Military Communications Conference</title><addtitle>milcom</addtitle><description>We present novel tunnelized second- and higher-order cyclostationary signal processing algorithms to simultaneously detect and characterize RF signals. 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We also demonstrate that such algorithms can detect and characterize signals for a highly adverse signal-to-interference-plus-noise ratio, even when multiple signals completely overlap in time and frequency.</description><subject>Bandwidth</subject><subject>cognitive radio</subject><subject>energy detection</subject><subject>higher-order cyclic cumulants</subject><subject>Multiaccess communication</subject><subject>Noise</subject><subject>second-order cyclostationary processing</subject><subject>Sensors</subject><subject>Signal processing algorithms</subject><subject>Spectrum sensing</subject><subject>Spread spectrum communication</subject><subject>Tunneling</subject><issn>2155-7578</issn><issn>2155-7586</issn><isbn>9780769551241</isbn><isbn>0769551246</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo9jstKw0AYRkdRUGrXLtzMC6TO_eKuhKqF1AqtSymTzD91JJ2EJFXq01tRXJ1vcz4OQteUTCgl9nYxL_LlYsII5RMq-AkaW22IVlZKygQ9RZeMSplpadTZ_9bmAo37_p0QQplRzNJL9LrepwR1_AKP80NVN_3ghtgk1x3wKm6Tq_Fz11TQ9zFt7_AUPzUfUONp23aNq97w0OCi-cxmCbrt0WihGrr9Dq8g_QhX6Dy4uofxH0fo5X62zh-zYvkwz6dFFhkxQ6ZdqQKxRoFngrlQSWu8NqUNuvRQCsIDp96zEEgpmbOSU6WNcI6Dt0pwPkI3v78RADZtF3fH_o3SXGom-DdGP1bs</recordid><startdate>20131101</startdate><enddate>20131101</enddate><creator>Spooner, Chad M.</creator><creator>Mody, Apurva N.</creator><creator>Chuang, Jack</creator><creator>Anthony, Michael P.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>20131101</creationdate><title>Tunnelized Cyclostationary Signal Processing: A Novel Approach to Low-Energy Spectrum Sensing</title><author>Spooner, Chad M. ; Mody, Apurva N. ; Chuang, Jack ; Anthony, Michael P.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i208t-7ab6f0986ed242afc598d78b9f7bdeb403f31dd2ff0b52a95316784aa3ed96433</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Bandwidth</topic><topic>cognitive radio</topic><topic>energy detection</topic><topic>higher-order cyclic cumulants</topic><topic>Multiaccess communication</topic><topic>Noise</topic><topic>second-order cyclostationary processing</topic><topic>Sensors</topic><topic>Signal processing algorithms</topic><topic>Spectrum sensing</topic><topic>Spread spectrum communication</topic><topic>Tunneling</topic><toplevel>online_resources</toplevel><creatorcontrib>Spooner, Chad M.</creatorcontrib><creatorcontrib>Mody, Apurva N.</creatorcontrib><creatorcontrib>Chuang, Jack</creatorcontrib><creatorcontrib>Anthony, Michael P.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE/IET Electronic Library</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Spooner, Chad M.</au><au>Mody, Apurva N.</au><au>Chuang, Jack</au><au>Anthony, Michael P.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Tunnelized Cyclostationary Signal Processing: A Novel Approach to Low-Energy Spectrum Sensing</atitle><btitle>MILCOM 2013 - 2013 IEEE Military Communications Conference</btitle><stitle>milcom</stitle><date>2013-11-01</date><risdate>2013</risdate><spage>811</spage><epage>816</epage><pages>811-816</pages><issn>2155-7578</issn><eissn>2155-7586</eissn><eisbn>9780769551241</eisbn><eisbn>0769551246</eisbn><coden>IEEPAD</coden><abstract>We present novel tunnelized second- and higher-order cyclostationary signal processing algorithms to simultaneously detect and characterize RF signals. Techniques that exploit second- and higher-order cyclostationary features to detect and classify signals possess many desirable properties. However, their pervasive use and hardware implementation have been hampered because such features are highly complex, and consume substantial processor energy. In this paper we present a novel concept, where we observe that severe but purposeful under-sampling of the signals through tunneling preserves sufficient exploitable cyclostationarity, even when the tunnel bandwidth is much smaller than the signal bandwidth. This phenomenon is then exploited to create a low complexity and flexible suite of algorithms to simultaneously detect and characterize signals using their tunneling-distorted cyclostationary features. We also demonstrate that such algorithms can detect and characterize signals for a highly adverse signal-to-interference-plus-noise ratio, even when multiple signals completely overlap in time and frequency.</abstract><pub>IEEE</pub><doi>10.1109/MILCOM.2013.143</doi><tpages>6</tpages></addata></record> |
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subjects | Bandwidth cognitive radio energy detection higher-order cyclic cumulants Multiaccess communication Noise second-order cyclostationary processing Sensors Signal processing algorithms Spectrum sensing Spread spectrum communication Tunneling |
title | Tunnelized Cyclostationary Signal Processing: A Novel Approach to Low-Energy Spectrum Sensing |
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