An application of the nonlinear stochastic estimation theory to the interference reduction in communication systems

An application of the nonlinear stochastic estimation theory to the problem of interference reduction among communication systems is analyzed. A significant overlapping of the spectra of the desired and interfering signals is assumed. The solution obtained takes the form of an extended Kalman filter. For such a solution some a priori data are needed, e.g. spectra and modulation techniques of the signals involved. Only angle-modulated signals are considered. In the simplest case, a receiver is obtained that corresponds to the MAP (maximum a posteriori) receiver. By taking more terms of the approximate solution to the Riccati equation, a superior solution for the present receiver is obtained. Digital simulations of the theoretical solutions confirm the suitability of the proposed method.