Abstract
An adaptive minimum bit error rate (MBER) linear multiuser detector (MUD) is proposed for DS-CDMA systems. Based on the approach of kernel density estimation for approximating the bit error rate (BER) from training data, a least mean squares (LMS) style adaptive algorithm is developed for training linear MUDs. Computer simulation results show that this adaptive MBER linear MUD outperforms two existing LMS-style adaptive MBER algorithms.
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