An efficient hybrid estimator for nonlinear channels in state space

Abstract

This paper presents a method for estimation of nonlinear communication channels using Gaussian wavelet estimator (GWE). Results obtained using this approach is compared with image enhanced interacting multiple model (IMM-IE) extracted from the literature. Comparison reveals that the IMM-IE and the GWE require the same number of Kalman filters, but the GWE extrapolates more initial conditions. If the performance of the two algorithms is equivalent, the IMM-IE is less complex, but GWE is technically efficient. Here, we have presented the state-space approach instead of the transfer function approach, as the state-space approach can be easily extended to nonlinear mixing systems. Moreover, the state-space approach not only gives an efficient internal description of the dynamic systems, but there also exist different possible equivalent state-space realizations.