Histogram Tests for Wideband Applications

Characterization and testing of analog-to-digital converters (ADCs) are important for many reasons. A histogram test is a common method to characterize the linearity features of an ADC. Two commonly used stimulus signals are sine waves and Gaussian noise. This paper presents a metrological comparison between Gaussian and sine-wave histogram tests for wideband applications, that is, we evaluate the performance of the characterization of the ADC and the usability of postcorrection. A postcorrection procedure involves the characterization of the ADC nonlinearity and then the use of this information by processing the ADC output samples to remove the distortion. The results show that the Gaussian histogram test gives reasonable accuracy in measuring nonlinearities. However, it does not result in a suitable model for postcorrection in wideband applications. A single-tone sine-wave histogram will be a better basis for postcorrection. The best result can be obtained if the lookup table is trained with several single-tone sine waves in the frequency band.     

Measuring Volterra Kernels of Analog-to-Digital Converters Using a Stepped Three-Tone Scan

The Volterra theory can be used to mathematically model nonlinear dynamic components such as analog-to-digital converters (ADCs). This paper describes how frequency-domain Volterra kernels of an ADC are determined from measurements. The elements of the Volterra theory are given, and practical issues are considered, such as methods for signal conditioning and finding the appropriate test signals scenario and suitable sampling frequency. The results show that, for the used pipeline ADC, the frequency dependence is significantly stronger for second-order difference products than for sum products and the linear frequency dependence was not as pronounced as that of the second-order Volterra kernel. It is suggested that the Volterra kernels have the symmetry properties of a specific box model, namely, the parallel Hammerstein system.