REDUCED COMPLEXITY NLMS ALGORITHM FOR BLIND ADAPTIVE MULTIUSER DETECTION (ThuPmOR8)

Author(s) : Kutluyil Dogancay (University of South Australia, Australia) Oguz Tanrikulu (Texas Instruments, United States)

Abstract : A reduced complexity normalized least-mean-square (NLMS) algorithm is presented for blind linear adaptive multiuser detection in synchronous direct-sequence CDMA systems. Selective partial updating is employed to reduce the computational complexity of the NLMS algorithm. The basic idea behind selective partial updating is to update only a small number of the adaptive filter coefficients at each iteration as identified by a selection criterion. It is shown that the reduced complexity selective partial update NLMS algorithm not only performs almost as well as the full-update NLMS algorithm in general, but in some cases it is also capable of outperforming the full-update algorithm. The performance of the proposed selective partial update algorithm is illustrated with computer simulations.

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