173 research outputs found

    축차 비교형 아날로그-디지털 변환기의 성능 향상을 위한 기법에 대한 연구

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    학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2016. 8. 김수환.This thesis is written about a performance enhancement technique for the successive-approximation-register analog-to-digital converter (SAR ADC). More specifically, it focuses on improving the resolution of the SAR ADC. The basic operation principles and the architecture of the conventional SAR ADC is examined. To gain insight on areas of improvement, a deeper look is taken at the building components of the SAR ADC. Design considerations of these components are discussed, along with the performance limiting factors in the resolution and bandwidth domains. Prior works which challenge these problems in order to improve the performance of the SAR ADC are presented. To design SAR ADCs, a high-level modeling is presented. This model includes various non-ideal effects that occur in the design and operation. Simulation examples are shown how the model is efficient and useful in the initial top-level designing of the SAR ADC. Then, the thesis proposes a technique that can enhance the resolution. The SAR ADC using integer-based capacitor digital-to-analog converter (CDAC) exploiting redundancy is presented. This technique improves the mismatch problem that arises with the widely used split-capacitor structure in the CDAC of the SAR ADC. Unlike prior works, there is no additional overhead of additional calibration circuits or reference voltages. A prototype SAR ADC which uses the integer-based CDAC exploiting redundancy is designed for automotive applications. Measurement results show a resolution level of 12 bits even without any form of calibration. Finally, the conclusion about the operation and effectiveness on the proposed technique is drawn.CHAPTER 1 INTRODUCTION 1 1.1 MOTIVATION 1 1.2 THESIS ORGANIZATION 5 CHAPTER 2 CONVENTIONAL SUCCESSIVE-APPROXIMATION-REGISTER ANALOG-TO-DIGITAL CONVERTERS 7 2.1 INTRODUCTION 7 2.2 OPERATION PRINCIPLE OF THE CONVENTIONAL SAR ADC 8 2.2.1. OVERVIEW OF THE OPERATION 8 2.2.2. SAMPLING PHASE 10 2.2.3. CONVERSION PHASE 11 2.3 STRUCTURE OF THE CONVENTIONAL SAR ADC 15 2.3.1. FULL STRUCTURE OF THE CONVENTIONAL SAR ADC 15 2.3.2. CAPACITOR DIGITAL-TO-ANALOG CONVERTER (CDAC) 17 2.3.3. COMPARATOR 21 2.3.4. CONTROL LOGIC 23 2.4 PERFORMANCE LIMITING FACTORS 24 2.4.1. RESOLUTION LIMITING FACTORS 24 2.4.2. OPERATION BANDWIDTH LIMITING FACTORS 28 2.5 PRIOR WORK 30 2.5.1. INTRODUCTION 30 2.5.2. SPLIT-CAPACITOR STRUCTURE OF THE CDAC 31 2.5.3. REDUNDANCY AND CDAC WEIGHT DISTRIBUTION 33 2.5.4. ASYNCHRONOUS CONTROL LOGIC 36 2.5.5. CALIBRATION TECHNIQUES 37 2.5.4. DOUBLE-SAMPLING TECHNIQUE FOR SAMPLING TIME REDUCTION 38 2.5.6. TWO-COMPARATOR ARCHITECTURE FOR COMPARATOR DECISION TIME REDUCTION 40 2.5.7. MAJORITY VOTING FOR RESOLUTION ENHANCEMENT 41 CHAPTER 3 MODELING OF THE SAR ADC 43 3.1 INTRODUCTION 43 3.2 WEIGHT DISTRIBUTION OF THE CAPACITOR DAC AND REDUNDANCY 44 3.3 SPLIT-CAPACITOR ARRAY TECHNIQUE 47 3.4 PARASITIC EFFECTS OF THE CAPACITOR DAC 48 3.5 MISMATCH MODEL OF THE CAPACITOR DAC 51 3.6 SETTLING ERROR OF THE DAC 53 3.7 COMPARATOR DECISION ERROR 58 3.8 DIGITAL ERROR CORRECTION 59 CHAPTER 4 SAR ADC WITH INTEGER-BASED SPLIT-CDAC EXPLOITING REDUNDANCY FOR AUTOMOTIVE APPLICATIONS 60 4.1 INTRODUCTION 60 4.2 MOTIVATION 61 4.3 PRIOR WORK ON RESOLVING THE SPLIT-CAPACITOR CDAC MISMATCH FOR THE SAR ADC 64 4.3.1. CONVENTIONAL SPLIT-CAPACITOR CDAC FOR THE SAR ADC 64 4.3.2. SPLITTING THE LAST STAGE OF THE LSB-SIDE OF THE CDAC 66 4.3.3. CALIBRATION OF THE NON-INTEGER MULTIPLE BRIDGE CAPACITOR 67 4.3.4. INTEGER-MULTIPLE BRIDGE CAPACITOR WITH LSB-SIDE CAPACITOR ARRAY CALIBRATION 68 4.3.5. OVERSIZED BRIDGE CAPACITOR WITH ADDITIONAL FRACTIONAL REFERENCE VOLTAGE 69 4.4 PROPOSED INTEGER-BASED CDAC EXPLOITING REDUNDANCY FOR THE SAR ADC 70 4.5 CIRCUIT DESIGN 72 4.5.1. PROPOSED INTEGER-BASED CDAC EXPLOITING REDUNDANCY FOR SAR ADC 72 4.5.2. COMPARATOR 74 4.5.3. CONTROL LOGIC 75 4.6 IMPLEMENTATION AND EXPERIMENTAL RESULTS 76 4.6.1. LAYOUT 76 4.6.2. MEASUREMENT RESULTS AND CONCLUSIONS 82 CHAPTER 5 CONCLUSION AND FUTURE WORK 86 5.1 CONCLUSION 86 5.2 FUTURE WORK 87 APPENDIX. SAR ADC USING THRESHOLD-CONFIGURING COMPARATOR FOR ULTRASOUND IMAGING SYSTEMS 89 BIBLIOGRAPHY 120Docto

    Design of capacitor array in 16-bit ultra high precision SAR ADC for the wearable electronics application

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    This paper proposes a 16-bit 6-channel high-voltage successive approximation register (SAR) ADC with an optimized 5+5+6 segmented capacitor array. The lower 10 bits of the capacitor array are all composed of unit capacitors without any calibration unit. Without calibration, the lower 10 bits of the capacitor array can ensure 10-bit conversion accuracy. Every of the upper 6 bits of the capacitor array contains a linearity calibration unit. The linearity error of the upper 6 bits is calibrated by the linearity calibration unit. The 16-bit is manufactured by a 0.6μm standard COMS process, and the total chip area of 6-channel ADC including pads is 6.6mm × 6.6mm. As for single channel SAR ADC, the area is 0.9mm × 2.0mm. The measurement results show that the effective conversion accuracy of the SAR ADC reaches 13 bits by using novel differential nonlinearity (DNL) and integral nonlinearity (INL) calibration methods. The power is 80mW, corresponding to a Figure of Merit (FOM) of 48 pJ/conv.-step

    Analysis, modeling and design of Successive Approach Analog-Digital Converters (SARADCs) with Digital Redundancy

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    Universidad de Sevilla. Máster Universitario en Microelectrónica: Diseño y Aplicaciones de Sistemas Micro/Nanométrico

    Low-power high-performance SAR ADC with redundancy and digital background calibration

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (p. 195-199).As technology scales, the improved speed and energy eciency make the successive- approximation-register (SAR) architecture an attractive alternative for applications that require high-speed and high-accuracy analog-to-digital converters (ADCs). In SAR ADCs, the key linearity and speed limiting factors are capacitor mismatch and incomplete digital-to-analog converter (DAC)/reference voltage settling. In this the- sis, a sub-radix-2 SAR ADC is presented with several new contributions. The main contributions include investigation of using digital error correction (redundancy) in SAR ADCs for dynamic error correction and speed improvement, development of two new calibration algorithms to digitally correct for manufacturing mismatches, design of new architecture to incorporate redundancy within the architecture itself while achieving 94% better energy eciency compared to conventional switching algorithm, development of a new capacitor DAC structure to improve the SNR by four times with improved matching, joint design of the analog and digital circuits to create an asynchronous platform in order to reach the targeted performance, and analysis of key circuit blocks to enable the design to meet noise, power and timing requirements. The design is fabricated in standard 1P9M 65nm CMOS technology with 1.2V supply. The active die area is 0.083mm² with full rail-to-rail input swing of 2.4V p-p . A 67.4dB SNDR, 78.1dB SFDR, +1.0/-0.9 LSB₁₂ INL and +0.5/-0.7 LSB₁₂ DNL are achieved at 50MS/s at Nyquist rate. The total power consumption, including the estimated calibration and reference power, is 2.1mW, corresponding to 21.9fJ/conv.- step FoM. This ADC achieves the best FoM of any ADCs with greater than 10b ENOB and 10MS/s sampling rate.by Albert Hsu Ting Chang.Ph.D

    Built-in self-test and self-calibration for analog and mixed signal circuits

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    Analog-to-digital converters (ADC) are one of the most important components in modern electronic systems. In the mission-critical applications such as automotive, the reliability of the ADC is critical as the ADC impacts the system level performance. Due to the aging effect and environmental changes, the performance of the ADC may degrade and even fail to meet the accuracy requirement over time. Built-in self-test (BIST) and self-calibration are becoming the ultimate solution to achieve lifetime reliability. This dissertation introduces two ADC testing algorithms and two ADC built-in self-test circuit implementations to test the ADC integral nonlinearity (INL) and differential nonlinearity (DNL) on-chip. In the first testing algorithm, the ultrafast stimulus error removal and segmented model identification of linearity errors (USER-SMILE) is developed for ADC built-in self-test, which eliminates the need for precision stimulus and reduces the overall test time. In this algorithm, the ADC is tested twice with a nonlinear ramp, instead of using a linear ramp signal. Therefore, the stimulus can be easily generated on-chip in a low-cost way. For the two ramps, there is a constant voltage shift in between. As the input stimulus linearity is completely relaxed, there is no requirement on the waveform of the input stimulus as long as it covers the ADC input range. In the meantime, the high-resolution ADC linearity is modeled with segmented parameters, which reduces the number of samples required for achieving high-precision test, thus saving the test time. As a result, the USER-SMILE algorithm is able to use less than 1 sample/code nonlinear stimulus to test high resolution ADCs with less than 0.5 least significant bit (LSB) INL estimation error, achieving more than 10-time test time reduction. This algorithm is validated with both board-level implementation and on-chip silicon implementation. The second testing algorithm is proposed to test the INL/DNL for multi-bit-per-stages pipelined ADCs with reduced test time and better test coverage. Due to the redundancy characteristics of multi-bit-per-stages pipelined ADC, the conventional histogram test cannot estimate and calibrate the static linearity accurately. The proposed method models the pipelined ADC nonlinearity as segmented parameters with inter-stage gain errors using the raw codes instead of the final output codes. During the test phase, a pure sine wave is sent to the ADC as the input and the model parameters are estimated from the output data with the system identification method. The modeled errors are then removed from the digital output codes during the calibration phase. A high-speed 12-bit pipelined ADC is tested and calibrated with the proposed method. With only 4000 samples, the 12-bit ADC is accurately tested and calibrated to achieve less than 1 LSB INL. The ADC effective number of bits (ENOB) is improved from 9.7 bits to 10.84 bits and the spurious-free dynamic range (SFDR) is improved by more than 20dB after calibration. In the first circuit implementation, a low-cost on-chip built-in self-test solution is developed using an R2R digital-to-analog converter (DAC) structure as the signal generator and the voltage shift generator for ADC linearity test. The proposed DAC is a subradix-2 R2R DAC with a constant voltage shift generation capability. The subradix-2 architecture avoids positive voltage gaps caused by mismatches, which relaxes the DAC matching requirements and reduces the design area. The R2R DAC based BIST circuit is fabricated in TSMC 40nm technology with a small area of 0.02mm^2. Measurement results show that the BIST circuit is capable of testing a 15-bit ADC INL accurately with less than 0.5 LSB INL estimation error. In the second circuit implementation, a complete SAR ADC built-in self-test solution using the USER-SMILE is developed and implemented in a 28nm automotive microcontroller. A low-cost 12-bit resistive DAC with less than 12-bit linearity is used as the signal generator to test and calibrate a SAR ADC with a target linearity of 12 bits. The voltage shift generation is created inside the ADC with capacitor switching. The entire algorithm processing unit for USER-SMILE algorithm is also implemented on chip. The final testing results are saved in the memory for further digital calibration. Both the total harmonic distortion (THD) and the SFDR are improved by 20dB after calibration, achieving -84.5dB and 86.5dB respectively. More than 700 parts are tested to verify the robustness of the BIST solution

    Successive-approximation-register based quantizer design for high-speed delta-sigma modulators

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    High-speed delta-sigma modulators are in high demand for applications such as wire-line and wireless communications, medical imaging, RF receivers and high-definition video processing. A high-speed delta-sigma modulator requires that all components of the delta-sigma loop operate at the desired high frequency. For this reason, it is essential that the quantizer used in the delta-sigma loop operate at a high sampling frequency. This thesis focuses on the design of high-speed time-interleaved multi-bit successive-approximation-register (SAR) quantizers. Design techniques for high-speed medium-resolution SAR analog-to-digital converters (ADCs) using synchronous SAR logic are proposed. Four-bit and 8-bit 5 GS/s SAR ADCs have been implemented in 65 nm CMOS using 8-channel and 16-channel time-interleaving respectively. The 4-bit SAR ADC achieves SNR of 24.3 dB, figure-of-merit (FoM) of 638 fJ/conversion-step and 42.6 mW power consumption, while the 8-bit SAR ADC achieves SNR of 41.5 dB, FoM of 191 fJ/conversion-step and 92.8 mW power consumption. High-speed operation is achieved by optimizing the critical path in the SAR ADC loop. A sampling network with a split-array with unit bridge capacitor topology is used to reduce the area of the sampling network and switch drivers

    DESIGN OF LOW-POWER LOW-VOLTAGE SUCCESSIVE-APPROXIMATION ANALOG-TO-DIGITAL CONVERTERS

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    Ph.DDOCTOR OF PHILOSOPH

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    Department of Electrical EngineeringA Sensor system is advanced along sensor technologies are developed. The performance improvement of sensor system can be expected by using the internet of things (IoT) communication technology and artificial neural network (ANN) for data processing and computation. Sensors or systems exchanged the data through this wireless connectivity, and various systems and applications are possible to implement by utilizing the advanced technologies. And the collected data is computed using by the ANN and the efficiency of system can be also improved. Gas monitoring system is widely need from the daily life to hazardous workplace. Harmful gas can cause a respiratory disease and some gas include cancer-causing component. Even though it may cause dangerous situation due to explosion. There are various kinds of hazardous gas and its characteristics that effect on human body are different each gas. The optimal design of gas monitoring system is necessary due to each gas has different criteria such as the permissible concentration and exposure time. Therefore, in this thesis, conventional sensor system configuration, operation, and limitation are described and gas monitoring system with wireless connectivity and neural network is proposed to improve the overall efficiency. As I already mentioned above, dangerous concentration and permissible exposure time are different depending on gas types. During the gas monitoring, gas concentration is lower than a permissible level in most of case. Thus, the gas monitoring is enough with low resolution for saving the power consumption in this situation. When detecting the gas, the high-resolution is required for the accurate concentration detecting. If the gas type is varied in the above situation, the amount of calculation increases exponentially. Therefore, in the conventional systems, target specifications are decided by the highest requirement in the whole situation, and it occurs increasing the cost and complexity of readout integrated circuit (ROIC) and system. In order to optimize the specification, the ANN and adaptive ROIC are utilized to compute the complex situation and huge data processing. Thus, gas monitoring system with learning-based algorithm is proposed to improve its efficiency. In order to optimize the operation depending on situation, dual-mode ROIC that monitoring mode and precision mode is implemented. If the present gas concentration is decided to safe, monitoring mode is operated with minimal detecting accuracy for saving the power consumption. The precision mode is switched when the high-resolution or hazardous situation are detected. The additional calibration circuits are necessary for the high-resolution implementation, and it has more power consumption and design complexity. A high-resolution Analog-to-digital converter (ADC) is kind of challenges to design with efficiency way. Therefore, in order to reduce the effective resolution of ADC and power consumption, zooming correlated double sampling (CDS) circuit and prediction successive approximation register (SAR) ADC are proposed for performance optimization into precision mode. A Microelectromechanical systems (MEMS) based gas sensor has high-integration and high sensitivity, but the calibration is needed to improve its low selectivity. Conventionally, principle component analysis (PCA) is used to classify the gas types, but this method has lower accuracy in some case and hard to verify in real-time. Alternatively, ANN is powerful algorithm to accurate sensing through collecting the data and training procedure and it can be verified the gas type and concentration in real-time. ROIC was fabricated in complementary metal-oxide-semiconductor (CMOS) 180-nm process and then the efficiency of the system with adaptive ROIC and ANN algorithm was experimentally verified into gas monitoring system prototype. Also, Bluetooth supports wireless connectivity to PC and mobile and pattern recognition and prediction code for SAR ADC is performed in MATLAB. Real-time gas information is monitored by Android-based application in smartphone. The dual-mode operation, optimization of performance and prediction code are adjusted with microcontroller unit (MCU). Monitoring mode is improved by x2.6 of figure-of-merits (FoM) that compared with previous resistive interface.clos
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