Nonlinearity Estimation for Specific Emitter Identification in Multipath Channels
We present a radio frequency (RF) front-end nonlinearity estimator that is based on the knowledge of a training sequence to perform specific emitter identification (SEI), which discerns radio emitters of interest. Design and fabrication variations provide unique signal signatures for each emitter, a...
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| Veröffentlicht in: | IEEE transactions on information forensics and security 2011-09, Vol.6 (3), p.1076-1085 |
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| creator | Ming-Wei Liu Doherty, J. F. |
| description | We present a radio frequency (RF) front-end nonlinearity estimator that is based on the knowledge of a training sequence to perform specific emitter identification (SEI), which discerns radio emitters of interest. Design and fabrication variations provide unique signal signatures for each emitter, and we extract those characteristics through the estimation of transmitter nonlinearity coefficients. The algorithm provides robust identification by first using alternative degrees of nonlinearities associated with symbol amplitudes for initial estimation, and then iteratively estimating the channel coefficients and distorted transmit symbols to overcome the inter-symbol interference (ISI) effect. The convergence and unbiasedness of the iterative estimator are demonstrated semi-analytically. Based on this analysis, we also trade error performance for complexity reduction using the regularity of the estimation process. The algorithm is applicable to a wide range of multi-amplitude modulation schemes, and we present an SEI system designed for an orthogonal-frequency-division multiplexing (OFDM) system over an empirical indoor channel model with associated numerical results. |
| doi_str_mv | 10.1109/TIFS.2011.2134848 |
| format | Article |
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F.</creator><creatorcontrib>Ming-Wei Liu ; Doherty, J. F.</creatorcontrib><description>We present a radio frequency (RF) front-end nonlinearity estimator that is based on the knowledge of a training sequence to perform specific emitter identification (SEI), which discerns radio emitters of interest. Design and fabrication variations provide unique signal signatures for each emitter, and we extract those characteristics through the estimation of transmitter nonlinearity coefficients. The algorithm provides robust identification by first using alternative degrees of nonlinearities associated with symbol amplitudes for initial estimation, and then iteratively estimating the channel coefficients and distorted transmit symbols to overcome the inter-symbol interference (ISI) effect. The convergence and unbiasedness of the iterative estimator are demonstrated semi-analytically. Based on this analysis, we also trade error performance for complexity reduction using the regularity of the estimation process. The algorithm is applicable to a wide range of multi-amplitude modulation schemes, and we present an SEI system designed for an orthogonal-frequency-division multiplexing (OFDM) system over an empirical indoor channel model with associated numerical results.</description><identifier>ISSN: 1556-6013</identifier><identifier>EISSN: 1556-6021</identifier><identifier>DOI: 10.1109/TIFS.2011.2134848</identifier><identifier>CODEN: ITIFA6</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Channel estimation ; Channels ; Communication system security ; Eigenvalues and eigenfunctions ; Emittance ; Estimation ; Estimators ; frequency-selective fading channels ; Linear approximation ; Mathematical models ; nonlinear distortion ; Nonlinearity ; OFDM ; Radio frequencies ; reconnaissance ; Studies ; Symbols ; Training ; Transmitters</subject><ispartof>IEEE transactions on information forensics and security, 2011-09, Vol.6 (3), p.1076-1085</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Sep 2011</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c390t-6956f4e4367bc7ecac31fc06d0185d757a5b8030b77a5c274670852e48e515c13</citedby><cites>FETCH-LOGICAL-c390t-6956f4e4367bc7ecac31fc06d0185d757a5b8030b77a5c274670852e48e515c13</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/5740592$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27901,27902,54733</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5740592$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Ming-Wei Liu</creatorcontrib><creatorcontrib>Doherty, J. F.</creatorcontrib><title>Nonlinearity Estimation for Specific Emitter Identification in Multipath Channels</title><title>IEEE transactions on information forensics and security</title><addtitle>TIFS</addtitle><description>We present a radio frequency (RF) front-end nonlinearity estimator that is based on the knowledge of a training sequence to perform specific emitter identification (SEI), which discerns radio emitters of interest. Design and fabrication variations provide unique signal signatures for each emitter, and we extract those characteristics through the estimation of transmitter nonlinearity coefficients. The algorithm provides robust identification by first using alternative degrees of nonlinearities associated with symbol amplitudes for initial estimation, and then iteratively estimating the channel coefficients and distorted transmit symbols to overcome the inter-symbol interference (ISI) effect. The convergence and unbiasedness of the iterative estimator are demonstrated semi-analytically. Based on this analysis, we also trade error performance for complexity reduction using the regularity of the estimation process. The algorithm is applicable to a wide range of multi-amplitude modulation schemes, and we present an SEI system designed for an orthogonal-frequency-division multiplexing (OFDM) system over an empirical indoor channel model with associated numerical results.</description><subject>Algorithms</subject><subject>Channel estimation</subject><subject>Channels</subject><subject>Communication system security</subject><subject>Eigenvalues and eigenfunctions</subject><subject>Emittance</subject><subject>Estimation</subject><subject>Estimators</subject><subject>frequency-selective fading channels</subject><subject>Linear approximation</subject><subject>Mathematical models</subject><subject>nonlinear distortion</subject><subject>Nonlinearity</subject><subject>OFDM</subject><subject>Radio frequencies</subject><subject>reconnaissance</subject><subject>Studies</subject><subject>Symbols</subject><subject>Training</subject><subject>Transmitters</subject><issn>1556-6013</issn><issn>1556-6021</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNpdkE1Lw0AQhhdRsFZ_gHgJXjylziT7kRyltFqoirSeQ7qd0C3pJu5uD_33JkR68DQvw_MOw8PYPcIEEfLn9WK-miSAOEkw5RnPLtgIhZCxhAQvzxnTa3bj_R6Ac5TZiH19NLY2lkpnwima-WAOZTCNjarGRauWtKmMjmYHEwK5aLElG_rNwBgbvR_rYNoy7KLprrSWan_Lrqqy9nT3N8fsez5bT9_i5efrYvqyjHWaQ4hlLmTFiadSbbQiXeoUKw1yC5iJrRKqFJsMUtioLulEcakgEwnxjAQKjemYPQ13W9f8HMmH4mC8prouLTVHX-SY54ngqicf_5H75uhs91wH9X8AQAfhAGnXeO-oKlrXuXCnAqHoFRe94qJXXPwp7joPQ8cQ0ZkXioPIk_QXVvR27w</recordid><startdate>201109</startdate><enddate>201109</enddate><creator>Ming-Wei Liu</creator><creator>Doherty, J. 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F.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c390t-6956f4e4367bc7ecac31fc06d0185d757a5b8030b77a5c274670852e48e515c13</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Algorithms</topic><topic>Channel estimation</topic><topic>Channels</topic><topic>Communication system security</topic><topic>Eigenvalues and eigenfunctions</topic><topic>Emittance</topic><topic>Estimation</topic><topic>Estimators</topic><topic>frequency-selective fading channels</topic><topic>Linear approximation</topic><topic>Mathematical models</topic><topic>nonlinear distortion</topic><topic>Nonlinearity</topic><topic>OFDM</topic><topic>Radio frequencies</topic><topic>reconnaissance</topic><topic>Studies</topic><topic>Symbols</topic><topic>Training</topic><topic>Transmitters</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ming-Wei Liu</creatorcontrib><creatorcontrib>Doherty, J. 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F.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Nonlinearity Estimation for Specific Emitter Identification in Multipath Channels</atitle><jtitle>IEEE transactions on information forensics and security</jtitle><stitle>TIFS</stitle><date>2011-09</date><risdate>2011</risdate><volume>6</volume><issue>3</issue><spage>1076</spage><epage>1085</epage><pages>1076-1085</pages><issn>1556-6013</issn><eissn>1556-6021</eissn><coden>ITIFA6</coden><abstract>We present a radio frequency (RF) front-end nonlinearity estimator that is based on the knowledge of a training sequence to perform specific emitter identification (SEI), which discerns radio emitters of interest. Design and fabrication variations provide unique signal signatures for each emitter, and we extract those characteristics through the estimation of transmitter nonlinearity coefficients. The algorithm provides robust identification by first using alternative degrees of nonlinearities associated with symbol amplitudes for initial estimation, and then iteratively estimating the channel coefficients and distorted transmit symbols to overcome the inter-symbol interference (ISI) effect. The convergence and unbiasedness of the iterative estimator are demonstrated semi-analytically. Based on this analysis, we also trade error performance for complexity reduction using the regularity of the estimation process. The algorithm is applicable to a wide range of multi-amplitude modulation schemes, and we present an SEI system designed for an orthogonal-frequency-division multiplexing (OFDM) system over an empirical indoor channel model with associated numerical results.</abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TIFS.2011.2134848</doi><tpages>10</tpages></addata></record> |
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| subjects | Algorithms Channel estimation Channels Communication system security Eigenvalues and eigenfunctions Emittance Estimation Estimators frequency-selective fading channels Linear approximation Mathematical models nonlinear distortion Nonlinearity OFDM Radio frequencies reconnaissance Studies Symbols Training Transmitters |
| title | Nonlinearity Estimation for Specific Emitter Identification in Multipath Channels |
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