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- W2187598772 abstract "An optimal multiuser detector in the weighted least squares (WLS) sense is derived. This detector, which includes the maximum likelihood multiuser detector as a special case, consists of two parts: a bank of linear fractionally chip spaced minimum mean squared error (MMSE) filters, and a nonlinear WLS metric minimizer. It is shown that the symbol spaced samples at the output of the MMSE filter bank provide a set of sufficient statistics for WLS detection. The relationship between the taps of a centralized decision feedback detector and the MMSE filter bank is derived. It is proven that all the necessary parameters for implementing the WLS detector can be realized by adaptively training a centralized decision feedback detector. Therefore, the WLS detector achieves optimal joint synchronization and data detection even in the pres- ence of colored noise, such as narrowband interference, without any a priori knowledge of the users' signatures, multipath channel taps or statistics of the colored noise. Significant features of the WLS detector are that: 1) the WLS detector is a generalization of the maximum likelihood multiuser detector that employs a bank of matched filters; 2) it is implemented adaptively; and 3) it has structural flexibility in terms of implementation complexity." @default.
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- W2187598772 date "2001-01-01" @default.
- W2187598772 modified "2023-09-27" @default.
- W2187598772 title "Optimal Adaptive Multiuser Detection in Unknown" @default.
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