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Title: Pattern classification based multiuser detectors for CDMA communication systems
Keywords: multiuser detection, multisurface method, DS-CDMA, support vector machines, multipath channels, steepest descent algorithm
Issue Date: 30-Jan-2006
Citation: CHETAN MAHENDRA (2006-01-30). Pattern classification based multiuser detectors for CDMA communication systems. ScholarBank@NUS Repository.
Abstract: This work deals with the problem of multiuser detection in direct sequence code division multiple access (DS-CDMA) systems in multipath environments. Existing multiuser detectors can be divided into two categories (i) low-complexity, poor-performance linear detectors and (ii) high-complexity, good-performance nonlinear detectors. In channels where orthogonality of code sequences is destroyed by multipath, detectors with linear complexity perform much worse than the nonlinear detectors. Here an Enhanced Multisurface Method (EMSM) for multiuser detection in multipath channels is proposed. EMSM is an intermediate piece-wise linear detection scheme with a run-time complexity linear in the number of users. Its bit error rate (BER) performance is compared with existing linear detectors, a nonlinear RBF detector trained by the new support vector learning algorithm and Verdua??s optimal detector. Simulations in multipath channels, for both synchronous and asynchronous cases, indicate that it always outperforms all other linear detectors, performing nearly as well as nonlinear detectors.
Appears in Collections:Master's Theses (Open)

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