Matrix analysis
Time series: data analysis and theory
Time series: data analysis and theory
Multiuser Detection
Effects of imperfect blind channel estimation on performance of linear CDMA receivers
IEEE Transactions on Signal Processing - Part I
Perturbation analysis for subspace decomposition with applications in subspace-based algorithms
IEEE Transactions on Signal Processing
Asymptotic performance analysis for signature waveform estimationin synchronous CDMA systems
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Blind multiuser channel estimation in asynchronous CDMA systems
IEEE Transactions on Signal Processing
Asymptotic analysis of blind multiuser detection with blind channel estimation
IEEE Transactions on Signal Processing
On the second-order statistics of the weighted sample covariance matrix
IEEE Transactions on Signal Processing
Blind multiuser detection: from MOE to subspace methods
IEEE Transactions on Signal Processing
Blind multiuser detection: a subspace approach
IEEE Transactions on Information Theory
Blind adaptive multiuser detection
IEEE Transactions on Information Theory
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We analyze the performance of two popular blind subspace-based signature waveform estimation techniques proposed by Wang and Poor and Buzzi and Poor for direct-sequence code division multiple-access (DS-CDMA) systems with unknown correlated noise. Using the first-order perturbation theory, analytical expressions for the mean-square error (MSE) of these algorithms are derived. We also obtain simple high SNR approximations of the MSE expressions which explicitly clarify how the performance of these techniques depends on the environmental parameters and how it is related to that of the conventional techniques that are based on the standard white noise assumption. Numerical examples further verify the consistency of the obtained analytical results with simulation results.