Signal processing with alpha-stable distributions and applications
Signal processing with alpha-stable distributions and applications
Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
A practical guide to heavy tails: statistical techniques and applications
A practical guide to heavy tails: statistical techniques and applications
Heavy-tailed probability distributions in the World Wide Web
A practical guide to heavy tails
Robust spatial filtering of coherent sources for wireless communications
Signal Processing
Robust constant modulus arrays based on fractional lower-order statistics
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05
Robust multiuser detection in non-Gaussian channels
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Fractionally spaced equalization using CMA: robustness to channelnoise and lack of disparity
IEEE Transactions on Signal Processing
Data block adaptive filtering algorithms for α-stable random processes
Digital Signal Processing
Capture Properties of the Generalized CMA in Alpha-Stable Noise Environment
Wireless Personal Communications: An International Journal
Adaptive blind equalization for MIMO systems under α-stable noise environment
IEEE Communications Letters
IEEE Transactions on Signal Processing
Space-time blind equalization under α-stable noise environment
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
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The presence of non-Gaussian ambient channel noise in wireless systems can degrade the performance of existing equalizers and signal detectors. In this paper, we investigate the problem of blind equalization in noisy communication channels by addressing the negative effects of heavy-tailed noise to the original constant modulus algorithm (CMA). We propose a new CM criterion employing fractional lower-order statistics (FLOS) of the equalizer input. The associated FLOS-CM blind equalizer, based on a stochastic gradient descent algorithm, is able to mitigate impulsive channel noise while restoring the constant modulus character of the transmitted communication signal. We perform an analytic study of the lock and capture properties of the proposed adaptive filter and we illustrate its improved convergence behavior and lower bit error rate through computer simulations with various types of noise environments that include the Gaussian and the alpha-stable.