RF transceiver parameter identification using regressive models

In this paper, we consider the nonlinear system modelling problem for on-chip testing of embedded mixed-signal systems. Behavioural modelling is proposed to characterize RF transceiver, in terms of input and output signals using simplified mathematical expressions. A Situation-Dependent AutoRegressive model with exogenous variable (SDARX) is introduced to approximate the conventional Nonlinear-ARX (NARX). The parameter search space is divided into a linear weight subspace and the nonlinear parameter subspace. A nonlinear parameter estimation strategy combines the Levenberg-Marquardt method (LMM) for nonlinear parameter optimization and the least- square method (LSM) for linear parameter estimation.