Signal processing with alpha-stable distributions and applications
Signal processing with alpha-stable distributions and applications
A new concept of adaptive beamforming for moving sources and impulse noise environment
Signal Processing - Special issue on current topics in adaptive filtering for hands-free acoustic communication and beyond
Wireless Communications: Principles and Practice
Wireless Communications: Principles and Practice
Space-Time Processing for CDMA Mobile Communications
Space-Time Processing for CDMA Mobile Communications
Robust multiuser detection in non-Gaussian channels
IEEE Transactions on Signal Processing
Analytic alpha-stable noise modeling in a Poisson field ofinterferers or scatterers
IEEE Transactions on Signal Processing
Automatica (Journal of IFAC)
Robust adaptive array for wireless communications
IEEE Journal on Selected Areas in Communications
Wideband code division multiple access
IEEE Journal on Selected Areas in Communications
Measurements and models of radio frequency impulsive noise for indoor wireless communications
IEEE Journal on Selected Areas in Communications
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A new robust M-estimation technique is developed for combating impulsive noise and multiuser interference in code-division multiple-access (CDMA) communication channels with a phased array receiver. A special power function of the proposed robust estimator is derived from the Huber's minimax robust estimation theory by minimizing a non-quadratic loss function of estimation residuals. Maximum peaks of this power function are used for estimation of communication signals as well as the direction-of-arrival (DOA). The produced theoretical analysis of the asymptotic accuracy of estimation is used for selection of the optimal minimax loss function. A strong advantage of the developed robust algorithm is a decreased sensitivity of the estimates with respect to actually unknown distributions of random noise and interferences. Simulation demonstrates that the proposed robust algorithms offer significant performance gain over the conventional least squares (LS) based estimator in terms of both BER and maximum user capacity.