Benchmarking of RF Measurement Systems for Digital Predistortion using Iterative Learning Control
Proc. 47th European Microwave Conf. (EuMC 2017), Nuremberg, Germany, Oct. 10-12, pp. 668-671 (2017).
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In this study iterative learning control (ILC) linearization is used to characterize the performance of a measurement system for modulated measurements and digital predistortion of RF power amplifiers. Without such linearization it is not possible to evaluate the dynamic range and effective bitresolution (ENOB) of the measurement system because of nonlinear and linear distortions. ILC allows linearization of periodic signals without the need of a predistorter model. With this information it is possible to determine in advance how much signal processing, e.g. averaging and oversampling of measurements, will be necessary to fulfill the linearity requirements. It is shown that using signal processing and ILC the effective resolution of a system using an 8 bit analog-to-digital converter on the receiver side can be increased by 4.3 bit without the need for additional hardware. Besides that it is found that special attention has to be devoted to the receiver nonlinearities to avoid projecting the nonlinearities to the device under test.
Ferdinand-Braun-Institut (FBH), Leibniz-Institut fuer Hoechstfrequenztechnik, 12489 Berlin, Germany
modulated measurements; digital predistortion; iterative learning control; dynamic range enhancement.