Abstract
A new higher order statistics-based adaptive interference canceler is introduced to mitigate narrowband and wideband interferences in environments where the interference is non-Gaussian and a reference signal, which is highly correlated with the interference, is available. The new scheme uses higher order statistics (HOS) of the primary and reference inputs and employs a gradient-type algorithm for updating the adaptive filter coefficients. The update equation of the HOS-based adaptive filter is independent of uncorrelated Gaussian noises and can mitigate the interference more effectively than adaptive filters based on second-order statistics. The performance of the. HOS-based adaptive filter is much less sensitive to the choice of the step size parameter than the adaptive filters based on the LMS algorithm. It is demonstrated, by means of extensive simulations, that the HOS-based filter can mitigate both narrowband and wideband interferences effectively. Comparisons with adaptive filters based on the LMS algorithm and second-order statistics are also presented in the paper

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