Chapter 8Characterization and Identification Techniques

8.1 Introduction

In the previous chapters, a thorough review of behavioral models proposed for the modeling and predistortion of wideband power amplifiers (PAs) and transmitters was presented. All these models can be seen as mathematical functions for which a set of coefficients needs to be identified. These coefficients are derived, using identification techniques, from measurements data acquired through the characterization of the device under test (DUT). Thus, the validity of a behavioral model and its accuracy will greatly depend, among others, on the characterization step. In fact, since the behavioral model coefficients are calculated solely from input and output measured data, the obtained model is able to take into consideration only the effects that are observed during the characterization step. For example, if measurements are performed with a test signal for which a DUT has a memoryless behavior, then a model derived from these measurements will be unable to predict the memory effects that will be present in the DUT if a wider bandwidth signal is used. This is true even if the model structure incorporates memory effects (such as the memory polynomial model). The accuracy of the model also depends on the model structure that is adopted and its ability to mimic all aspects of the observed behavior. As matter of fact, if the DUT exhibits memory effects during the measurements, the appropriate model structure should ...

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