Dynamic convergence analysis of adaptive nonlinear filters for narrowband interference rejection in spread spectrum systems

In CDMA systems by exploiting the binary nature of the CDMA signal, adaptive nonlinear filters can significantly outperform their linear counterparts at rejecting narrowband interference (NBI). Because the NBI is time varying in many scenarios, we characterize the ability of adaptive nonlinear filters to track dynamically the NBI. We study the dynamic convergence behavior of the nonlinear predictor proposed by Vijayan and Poor, adapted by the LMS and normalized LMS algorithms using two analytical methods: the independence method and the small step-size method. We verify our theoretical mean square error trajectories using Monte Carlo simulations