Identification of nonlinear channels in digital transmission systems

Abstract

Nonlinearity in digital transmission channels has long been an important problem in digital communications. Being able to identify the nonlinear characteristics of the channels can help in the design of the nonlinear equalizer. The authors consider identification of PSK and QAM nonlinear channels which can be expressed as a third-order complex-valued Volterra series. Based on higher-order moment analysis, they derive a simple algorithm to identify the Volterra kernels. In addition, it is shown that, for properly designed input sequences, the estimate obtained by the proposed method is equal to the optimum minimum mean square error solution.<>