Achievable ADC Performance by Postcorrection Utilizing Dynamic Modeling of the Integral Nonlinearity.

Journal on Advances in Signal Processing (Impact Factor: 0.78). 01/2008; 2008. DOI: 10.1155/2008/497187
Source: DBLP


There is a need for a universal dynamic model of analog-to-digital converters (ADC's) aimed for postcorrection. However, it is complicated to fully describe the properties of an ADC by a single model. An alternative is to split up the ADC model in different components, where each component has unique properties. In this paper, a model based on three components is used, and a performance analysis for each component is presented. Each component can be postcorrected individually and by the method that best suits the application. The purpose of postcorrection of an ADC is to improve the performance. Hence, for each component, expressions for the potential improvement have been developed. The measures of performance are total harmonic distortion (THD) and signal to noise and distortion (SINAD), and to some extent spurious-free dynamic range (SFDR).

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Available from: Niclas Björsell, Oct 01, 2015
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    • "The specific relation between polynomial coefficients and harmonic power can be expressed in general [14]. The same analysis can be done when the input signal is supposed to be two tone signals; it will cause the production of more terms, the specific terms harmonics, and intermodulation. "
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    ABSTRACT: Analog-to-information converter (AIC) plays an important role in the compressed sensing system; it has the potential to significantly extend the capabilities of conventional analog-to-digital converter. This paper evaluates the impact of AIC nonlinearity on the dynamic performance in practical compressed sensing system, which included the nonlinearity introduced by quantization as well as the circuit non-ideality. It presents intuitive yet quantitative insights into the harmonics of quantization output of AIC, and the effect of other AIC nonlinearity on the spurious dynamic range (SFDR) performance is also analyzed. The analysis and simulation results demonstrated that, compared with conventional ADC-based system, the measurement process decorrelates the input signal and the quantization error and alleviate the effect of other decorrelates of AIC, which results in a dramatic increase in spurious free dynamic range (SFDR).
    05/2014; 2014:143693. DOI:10.1155/2014/143693
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    • "Some recent techniques are based on the modeling of the INL with complementary components: the low frequency component (LFC) and high frequency component (HFC) [15], [16]. It is also possible to extend the model to the dynamic INL (DLFC) to take into account the variation of the INL according to the signal or sampling frequency [17], [18]. Each INL component can be extracted with a specific test technique (generally based on histograms) with a reduced and optimal number of samples. "
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    ABSTRACT: The semiconductor industry tends to constantly increase the performances of developed systems with an ever-shorter time-to-market. In this context, the conventional strategy for mixed-signal component design, which is based only on analog design effort, will no longer be suitable. In this paper, a digital correction technique is presented for analog-to-digital converters (ADCs). The idea is to use a lookup table (LUT) for the online correction of integral nonlinearity (INL). The main challenge for this kind of technique is the cost in time and resources to estimate the actual INL of the ADC needed to load the LUT. In this paper, we propose to extract INL with a very rapid procedure based on spectral analysis. We validate our technique on a 12-bit folding-and-interpolating ADC and we demonstrate that the correction is efficient for a large range of application fields.
    IEEE Transactions on Instrumentation and Measurement 04/2011; 60(3-60):768 - 775. DOI:10.1109/TIM.2010.2060222 · 1.79 Impact Factor
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    • "Another type of error common to RF devices is harmonic distortion generated by the nonlinear components. This harmonic distortion is reflected in the INL by a polynomial-shaped variation in the output code domain; its coefficients are related to the harmonics amplitudes or levels [11]. The polynomial behavior of the INL is clearly Fig. 3. Average INL for 15 sequences corresponding to test frequencies in the interval 30–90 MHz for a 12-bit pipelined ADC (AD9430). "
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    ABSTRACT: Integral nonlinearity (INL) for pipelined analog-digital converters (ADCs) operating at RF is measured and characterized. A parametric model for the INL of pipelined ADCs is proposed, and the corresponding least-squares problem is formulated and solved. The INL is modeled both with respect to the converter output code and the frequency stimuli, which is dynamic modeling. The INL model contains a static and a dynamic part. The former comprises two 1-D terms in ADC code that are a sequence of zero-centered linear segments and a polynomial term. The 2-D dynamic part consists of a set of polynomials whose parameters are dependent on the ADC input stimuli. The INL modeling methodology is applied to simulated and experimental data from a 12-bit commercial ADC running at 210 mega samples per second. It is demonstrated that the developed methodology is an efficient way to capture the INL of nowadays ADCs running at RF, and it is believed that the methodology is powerful for INL-based ADC postcorrection in wideband applications.
    IEEE Transactions on Instrumentation and Measurement 11/2010; DOI:10.1109/TIM.2010.2045551 · 1.79 Impact Factor
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