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For joint blind channel estimation and multiuser detection in direct-sequence code division multiple access (DS-CDMA) systems, a combined scheme is proposed, which couples the recursive least-squares (RLS) adaptations and the PASTd subspace tracking algorithm. A major advantage of the RLS-PASTd algorithm is that it admits an adaptive implementation with low computational complexity instead of singular value decomposition. Simulation results demonstrate the fast tracking capability and high steady-state estimation accuracy of the proposed algorithm in both the time-invariant and time-variant environments [ABSTRACT FROM PUBLISHER]

In statistical signal processing, the sequential Monte Carlo (SMC) method is powerful and can approach the theoretical optima. However, its computational complexity is usually very high, especially in multiple-input multiple-output (MIMO) systems. This paper presents a new low-complexity SMC (LC-SMC) algorithm for blind detection in MIMO systems, the main idea of which is to shrink the sampling space via channel estimation which is initialized using the first differentially modulated symbol and then updated using the Monte Carlo samples. Since the a posteriori probability of the transmitted symbols can be calculated separately by each transmit antenna, the proposed LC-SMC algorithm is not only computationally efficient, as compared to the original SMC whose complexity grows exponentially with the number of transmit antennas, but also makes blind turbo receiver more feasible for multilevel/phase modulations. Simulation results are presented to demonstrate the effectiveness of the LC-SMC algorithm. [ABSTRACT FROM AUTHOR]

Focuses on a study which proposed an adaptive recursive-least squares algorithm with prewhitening for blind source separation using the natural gradient on the Stiefel manifold to minimize a nonlinear principle component analysis criterion. Problem formulation and the nonlinear principal component analysis; Adaptive algorithms using a natural gradient; Comparison with other related algorithms.