Modeling Analog to Digital Converters at Radio Frequency

This work considers behavior modeling of analog to digital converters with applications in the radio frequency range, including the field of telecommunication as well as test and measurement instrumentation, where the conversion from analog to digital signals often is a bottleneck in performance. The models are intended to postprocess output data from the converter and thereby improve the performance of the digital signal. By building a model of practical converters and the way in which they deviate from ideal, imperfections can be corrected using post-correction methods. Behavior modeling implies generation of a suitable stimulus, capturing the output data, and characterizing a model. The demands on the test setup are high for converters in the radio frequency range. The test-bed used in this thesis is composed of commercial state-of-the-art instruments and components designed for signal conditioning and signal capture. Further, in this thesis, different stimuli are evaluated, theoretically as well as experimentally. There are a large number of available model structures for dynamic nonlinear systems. In order to achieve a parameter efficient model structure, a Volterra model was used as a starting-point, which can describe any weak nonlinear system with fading memory, such as analog to digital converters. However, it requires a large number of coefficients; for this reason the Volterra model was reduced to a model structure with fewer parameters, by comparing the symmetry properties of the Volterra kernels with the symmetries from other models. An alternative method is the Kautz-Volterra model, which has the same general properties as the Volterra model, but with fewer parameters. This thesis gives experimental results of the Kautz-Volterra model, which will be interesting to apply in a post-correction algorithm in the future. To cover behavior not explained by the dynamic nonlinear model, a complementary piecewise linear model component is added. In this thesis, a closed form solution to the estimation problem for both these model components is given. By gradually correcting for each component the performance will improve step by step. In this thesis, the relation between a given component and the performance of the converter is given, as well as potential for improvement of an optimal post-correction.