The paper is concerned with an identification-based predistortion scheme for compensating nonlinearity of high power amplifiers (HPA). The identification algorithms for the Wiener-Hammerstein nonlinear model are developed in the frequency domain. By approximately modeling the nonlinear distortion part in HPA by polynomial or spline functions, and introducing linear distortion parts in the input and output of the nonlinear element, the iterative identification schemes are proposed to estimate all the uncertain parameters and to construct an inverse system for the predistortion.

This paper is concerned with blind identification of a nonminimum phase transfer function model. By over-sampling the output at a higher rate than the input, it is shown that its input-output relation can be described by a single input multiple output model (SIMO) with a common denominator polynomial. Based on the model expression, we present an algorithm to estimate numerator polynomials and common denominator polynomial in a blind manner. Furthermore, identifiability of the proposed scheme is clarified, and some numerical results are given for demonstrating its effectiveness.

A new identification algorithm based on output over-sampling scheme is proposed for a IIR model whose input signal can not be available directly. By using only an output signal sampled at higher rate than unknown input, parameters of the IIR model can be identified. It is clarified that the consistency of the obtained parameter estimates is assured under some specified conditions. Further an efficient recursive algorithm for blind parameter estimation is also given for practical applications. Simulation results demonstrate its effectiveness in both system and channel identification.