Multiuser Detection in CDMA Mobile Terminals
Multiuser Detection in CDMA Mobile Terminals
Statistical Digital Signal Processing and Modeling
Statistical Digital Signal Processing and Modeling
Time Series Analysis and Its Applications (Springer Texts in Statistics)
Time Series Analysis and Its Applications (Springer Texts in Statistics)
IEEE Transactions on Signal Processing
The Kalman filter as the optimal linear minimum mean-squared error multiuser CDMA detector
IEEE Transactions on Information Theory
An asynchronous multiuser CDMA detector based on the Kalman filter
IEEE Journal on Selected Areas in Communications
Receivers and CQI measures for MIMO-CDMA systems in frequency-selective channels
EURASIP Journal on Applied Signal Processing
An efficient circulant MIMO equalizer for CDMA downlink: algorithm and VLSI architecture
EURASIP Journal on Applied Signal Processing
A division algebraic framework for multidimensional support vector regression
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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An efficient method for equalization of downlink CDMA channels is presented. By describing the observed signal in terms of a state-space model, the method employs the Kalman filter (KF) to achieve an unbiased signal estimate satisfying the linear minimum mean-squared error (LMMSE) criterion. The state-space model is realized at the symbol and chip levels. With the symbol-level model, the KF is used to estimate the transmitted chips that correspond to each symbol interval; whereas at the chip level, the transmitted chips are estimated individually. The symbol-level KF has a built-in tracking capability that takes advantage of the a priori known scrambling sequence, which renders the transmitted signal nonstationary. The chip-level KF reduces the complexity of the symbol-level KF significantly by ignoring the nonstationarity introduced by scrambling. A simple method for further reducing the KF complexity is also presented. The computational complexity of the proposed technique is analyzed and compared with that of several linear approaches based on finite-impulse response (FIR) filtering. Simulations under realistic channel conditions are carried out which indicate that the KF-based approach is superior to FIR equalizers by 1-2 dBs in error-rate performance.