Adaptive signal processing
Adaptive filter theory
Multiuser Detection
A time-domain feedback analysis of filtered-error adaptive gradientalgorithms
IEEE Transactions on Signal Processing
A feedback approach to the steady-state performance of fractionallyspaced blind adaptive equalizers
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
A stochastic gradient adaptive filter with gradient adaptive stepsize
IEEE Transactions on Signal Processing
Performance analysis of the linearly constrained constant modulus algorithm-based multiuser detector
IEEE Transactions on Signal Processing
Misadjustment and tracking analysis of the constant modulus array
IEEE Transactions on Signal Processing
The constant modulus array for cochannel signal copy and directionfinding
IEEE Transactions on Signal Processing
Analysis and implementation of variable step size adaptivealgorithms
IEEE Transactions on Signal Processing
A multistep size (MSS) frequency domain adaptive filter
IEEE Transactions on Signal Processing
Recursive least squares constant modulus algorithm for blind adaptive array
IEEE Transactions on Signal Processing
A unified approach to the steady-state and tracking analyses ofadaptive filters
IEEE Transactions on Signal Processing
A variable step size LMS algorithm
IEEE Transactions on Signal Processing
A robust variable step-size LMS-type algorithm: analysis andsimulations
IEEE Transactions on Signal Processing
Experimental results of localization of moving underwater signal byadaptive beamforming
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing - Part I
Relationships between the constant modulus and Wiener receivers
IEEE Transactions on Information Theory
A random beamforming technique in MIMO systems exploiting multiuser diversity
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Signal Processing
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In this paper, we propose two low-complexity adaptive step size mechanisms to enhance the performance of stochastic gradient (SG) algorithms for adaptive beamforming. The beamformer is designed according to the constrained constant modulus (CCM) criterion and the proposed mechanisms are employed in the SG algorithm for implementation. A complexity comparison is provided to show their advantages over existing methods, and a sufficient condition for the convergence of the mean weight vector is established. Theoretical expressions of the excess mean-squared error (EMSE), in both the steady-state and tracking cases, are derived based on the energy conservation approach. The effects of multiple access interference (MAI) and additive noise are considered. Simulation experiments are presented for both the stationary and non-stationary scenarios, illustrating that the proposed algorithms achieve superior performance compared with existing methods, and verifying the accuracy of the analyses.