Detection schemes for weak signals in first-order moving average of impulsive noise

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dc.contributor.authorKim, IJko
dc.contributor.authorPark, SRko
dc.contributor.authorSong, Iickhoko
dc.contributor.authorLee, Jko
dc.contributor.authorKwon, Hko
dc.contributor.authorYoon, Sko
dc.date.accessioned2007-07-30T12:22:04Z-
dc.date.available2007-07-30T12:22:04Z-
dc.date.created2012-02-06-
dc.date.created2012-02-06-
dc.date.issued2007-01-
dc.identifier.citationIEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, v.56, pp.126 - 133-
dc.identifier.issn0018-9545-
dc.identifier.urihttp://hdl.handle.net/10203/955-
dc.description.abstractIn this paper, the detection of weak signals in additive noise described by the first-order moving average (FOMA) of an impulsive process is considered. Specifically, decision regions of the maximum likelihood (ML) and suboptimum NIL (S-ML) detectors are derived in the FOMA noise model, and specific examples of the ML and S-NIL decision regions are obtained. The ML and S-ML detectors are employed in the antipodal signaling system and compared in terms of bit error rate in an impulsive noise environment. Numerical results show that the S-ML detector, despite its reduced complexity and simpler structure, exhibits practically the same performance as the optimum ML detector. It is also observed that the performance gap between detectors for FOMA and independent and identically distributed noise becomes larger as the degree of noise impulsiveness increases.-
dc.description.sponsorshipMinistry of Science and Technology (MOST) of Korea under the National Research Laboratory (NRL) Program of the Korea Science and Engineering Foundation (KOSEF)en
dc.languageEnglish-
dc.language.isoen_USen
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC-
dc.subjectOPTIMUM BAYES DETECTION-
dc.subjectNON-GAUSSIAN NOISE-
dc.subjectDEPENDENT NOISE-
dc.subjectMODELS-
dc.titleDetection schemes for weak signals in first-order moving average of impulsive noise-
dc.typeArticle-
dc.identifier.wosid000243887800012-
dc.identifier.scopusid2-s2.0-33847632494-
dc.type.rimsART-
dc.citation.volume56-
dc.citation.beginningpage126-
dc.citation.endingpage133-
dc.citation.publicationnameIEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY-
dc.identifier.doi10.1109/TVT.2006.883727-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorSong, Iickho-
dc.contributor.nonIdAuthorKim, IJ-
dc.contributor.nonIdAuthorPark, SR-
dc.contributor.nonIdAuthorLee, J-
dc.contributor.nonIdAuthorKwon, H-
dc.contributor.nonIdAuthorYoon, S-
dc.type.journalArticleArticle-
dc.subject.keywordAuthordependent noise-
dc.subject.keywordAuthordetection-
dc.subject.keywordAuthorfirst-order moving average (FOMA)-
dc.subject.keywordAuthorimpulsive noise-
dc.subject.keywordAuthorsuboptimum scheme-
dc.subject.keywordAuthorweak signal-
dc.subject.keywordPlusOPTIMUM BAYES DETECTION-
dc.subject.keywordPlusNON-GAUSSIAN NOISE-
dc.subject.keywordPlusDEPENDENT NOISE-
dc.subject.keywordPlusMODELS-
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