Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/806
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dc.contributor.authorGajbhiye, M R-
dc.contributor.authorSathpathy, J K-
dc.date.accessioned2009-04-21T03:01:46Z-
dc.date.available2009-04-21T03:01:46Z-
dc.date.issued2008-
dc.identifier.citationIEEE Region 10 Conference TENCON 2008 - 2008, TENCON 2008. HYDERABAD, P 1-6en
dc.identifier.urihttp://dx.doi.org/10.1109/TENCON.2008.4766759-
dc.identifier.urihttp://hdl.handle.net/2080/806-
dc.descriptionCopyright for the paper belongs to IEEEen
dc.description.abstractThe performance of the minimum mean squared error (MMSE) based adaptive multiuser detection (MUD) of direct-sequence code-division multiple access (DS-CDMA) signals in dispersive and non-dispersive channels is considered. DS-CDMA is a popular multiple-access technology for wireless communication. However its performance is limited by multiple-access interference (MAI) and multipath distortion. Adaptive techniques for detection of DS-CDMA signals improves the performance of the CDMA system by reducing interference among users by employing two major types of adaptive technique called least mean squares (LMS) and recursive least square (RLS) in non-dispersive channels. In this paper the diversity scheme called maximum ratio combining (MRC) as preprocessor to the adaptive MMSE detector of DS-CDMA system in dispersive channel is introduced. Simulations have proved its better performance compared with the conventional Match Filter detector, performing nearly as well as single user case.en
dc.format.extent229068 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.publisherIEEEen
dc.subjectcode division multiple accessen
dc.subjectdispersive channelsen
dc.subjectleast mean squares methodsen
dc.subjectmultipath channelsen
dc.subjectmultiuser detectionen
dc.subjectspread spectrum communicationen
dc.subjectwireless channelsen
dc.titlePerformance analysis of MMSE based adaptive multiuser detection of DS-CDMA signals in dispersive and non-dispersive channelsen
dc.typeArticleen
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