Interference rejection in direct-sequence spread spectrum communication systems based on higher-order statistics and genetic algorithm

A new higher order statistics (HOS) and genetic algorithm (GA)-based interference rejection filter is introduced. When a reference signal, which is highly correlated with the interference, is available, the new method uses GA to update the adaptive filter coefficients after the HOS of the primary and reference signal are computed. Compared with the adaptive filters based on second-order statistics, the HOS and GA-based filter can reject the interference more efficiently and is independent of uncorrelated Gaussian noise. The HOS and GA-based adaptive filter tends to converge to the optimum and is much less sensitive to the choice of the step size parameter than the adaptive filters based on the gradient algorithm. Computer simulations show that the method can reject narrowband interference efficiently.