<p>An analog-to-digital converter (ADC) is a link between the analog and digital domains and plays a vital role in modern mixed signal processing systems. There are several architectures, for example flash ADCs, pipeline ADCs, sigma delta ADCs,successive approximation (SAR) ADCs and time interleaved ADCs. Among the various architectures, the pipeline ADC offers a favorable trade-off between speed,power consumption, resolution, and design effort. The commonly used applications of pipeline ADCs include high quality video systems, radio base stations,Ethernet, cable modems and high performance digital communication systems.Unfortunately, static errors like comparators offset errors, capacitors mismatch errors and gain errors degrade the performance of the pipeline ADC. Hence, there is need for accuracy enhancement techniques. The conventional way to overcome these mentioned errors is to calibrate the pipeline ADC after fabrication, the so-called post fabrication calibration techniques. But environmental changes like temperature and device aging necessitates the recalibration after regular intervals of time, resulting in a loss of time and money. A lot of effort can be saved if the digital outputs of the pipeline ADC can be used for the estimation and correctionof these errors, further classified as foreground and background techniques. In this thesis work, an algorithm is proposed that can estimate 10% inter stage gain errors in pipeline ADC without any need for a special calibration signal. The efficiency of the proposed algorithm is investigated on an 8-bit pipeline ADC architecture.The first seven stages are implemented using the 1.5-bit/stage architecture whilethe last stage is a one-bit flash ADC. The ADC and error correction algorithms simulated in Matlab and the signal to noise and distortion ratio (SNDR) is calculated to evaluate its efficiency.</p>
Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:liu-59248 |
Date | January 2010 |
Creators | javeed, khalid |
Publisher | Linköping University, Electronic Devices |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, text |
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