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Noncoherent sequential code acquisition based on simplified maximum likelihood ratios

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dc.contributor.authorKwon, H-
dc.contributor.authorSong, I-
dc.contributor.authorYoon, S-
dc.contributor.authorLee, J-
dc.contributor.authorKim, SY-
dc.contributor.authorChung, BH-
dc.date.accessioned2022-02-17T03:41:43Z-
dc.date.available2022-02-17T03:41:43Z-
dc.date.created2022-02-17-
dc.date.issued2005-08-
dc.identifier.issn0165-1684-
dc.identifier.urihttps://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/25162-
dc.description.abstractIn this paper, we consider the noncoherent code acquisition problem using sequential schemes. To alleviate the computational complexity of the maximum likelihood method, simplified schemes are proposed and analyzed for the truncated sequential probability ratio test. The performance of the simplified and original schemes are compared in additive white Gaussian noise and slowly varying fading channels. Numerical results show that the proposed schemes have essentially the same performance as the original schemes while allowing simpler structures. (c) 2005 Elsevier B.V. All rights reserved.-
dc.language영어-
dc.language.isoen-
dc.publisherELSEVIER SCIENCE BV-
dc.subjectBESSEL-FUNCTIONS-
dc.titleNoncoherent sequential code acquisition based on simplified maximum likelihood ratios-
dc.typeArticle-
dc.contributor.affiliatedAuthorChung, BH-
dc.identifier.doi10.1016/j.sigpro.2005.02.009-
dc.identifier.scopusid2-s2.0-19844367430-
dc.identifier.wosid000230185500008-
dc.identifier.bibliographicCitationSIGNAL PROCESSING, v.85, no.8, pp.1563 - 1571-
dc.relation.isPartOfSIGNAL PROCESSING-
dc.citation.titleSIGNAL PROCESSING-
dc.citation.volume85-
dc.citation.number8-
dc.citation.startPage1563-
dc.citation.endPage1571-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.subject.keywordPlusBESSEL-FUNCTIONS-
dc.subject.keywordAuthorsequential code acquisition-
dc.subject.keywordAuthormaximum likelihood estimate-
dc.subject.keywordAuthorBessel function-
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