ADAPTIVE INTERFERENCE CANCELER FOR NARROW-BAND AND WIDE-BAND INTERFERENCES USING HIGHER-ORDER STATISTICS

A new higher order statistics-based adaptive interference canceler is introduced to mitigate narrowband and wideband interferences in enviro nments where the interference is non-Gaussian and a reference signal, which is highly correlated with the interference, is available. The ne w scheme uses higher order statistics (HOS) of the primary and referen ce inputs and employs a gradient-type algorithm for updating the adapt ive filter coefficients. The update equation of the HOS-based adaptive filter is independent of uncorrelated Gaussian noises and can mitigat e the interference more effectively than adaptive filters based on sec ond-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, b y means of extensive simulations, that the HOS-based filter can mitiga te both narrowband and wideband interferences effectively. Comparisons with adaptive filters based on the LMS algorithm and second-order sta tistics are also presented in the paper.