Design Techniques for High-Performance SAR A/D Converters

The design of electronics needs to account for the non-ideal characteristics of the device technologies used to realize practical circuits. This is particularly important in mixed analog-digital design since the best device technologies are very different for digital compared to analog circuits. One solution for this problem is to use a calibration correction approach to remove the errors introduced by devices, but this adds complexity and power dissipation, as well as reducing operation speed, and so must be optimised. This thesis addresses such an approach to improve the performance of certain types of analog-to-digital converter (ADC) used in advanced telecommunications, where speed, accuracy and power dissipation currently limit applications. The thesis specifically focuses on the design of compensation circuits for use in successive approximation register (SAR) ADCs. ADCs are crucial building blocks in communication systems, in general, and for mobile networks, in particular. The recently launched fifth generation of mobile networks (5G) has required new ADC circuit techniques to meet the higher speed and lower power dissipation requirements for 5G technology. The SAR has become one of the most favoured architectures for designing high-performance ADCs, but the successive nature of the circuit operation makes it difficult to reach ∼GS/s sampling rates at reasonable power consumption. Here, two calibration techniques for high-performance SAR ADCs are presented. The first uses an on-chip stochastic-based mismatch calibration technique that is able to accurately compute and compensate for the mismatch of a capacitive DAC in a SAR ADC. The stochastic nature of the proposed calibration method enables determination of the mismatch of the CAPDAC with a resolution much better than that of the DAC. This allows the unit capacitor to scale down to as low as 280aF for a 9-bit DAC. Since the CAP-DAC causes a large part of the overall dynamic power consumption and directly determines both the sizes of the driving and sampling switches and the size of the input capacitive load of the ADC and the kT/C noise power, a small CAP-DAC helps the power efficiency. To validate the proposed calibration idea, a 10-bit asynchronous SAR ADC was fabricated in 28-nm CMOS. Measurement results show that the proposed stochastic calibration improves the ADC’s SFDR and SNDR by 14.9 dB, 11.5 dB, respectively. After calibration, the fabricated SAR ADC achieves an ENOB of 9.14 bit at a sampling rate of 85 MS/s, resulting in a Walden FoM of 10.9 fJ/c-s. The second calibration technique is a timing-skew calibration for a time-interleaved (TI) SAR ADC that calibrates/computes the inter-channel timing and offset mismatch simultaneously. Simulation results show the effectiveness of this calibration method. When used together, the proposed mismatch calibration technique and the timing-skew calibration technique enables a TI SAR ADC to be designed that can achieve a sampling rate of ∼GS/s with 10-bit resolution and a power consumption as low as ∼10mW; specifications that satisfy the requirements of 5G technology

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

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

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

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

Plasmonic color filter array, high performance analog to digital converter architectures and novel circuit techniques

Part I: Plasmonic color filters can be manufactured at lower cost since they can be fabricated in single lithographic process step as compared to Fabry-Perot based filters. In addition, they have narrow passband making resolving sharp features in sample spectrum possible. Due to these benefits, in this thesis, Plasmonic color filters are investigated as alternative to conventional color filters and their feasibility for spectroscopy demonstrated through reconstruction of 6 sample spectra by using a set of 20 color filters. The error in reconstructed sample spectra is less than 0.137 root mean squared error across all samples. Part II: A novel 12-bit pipelined successive approximation analog to digital converter is investigated for high speed data conversion. The design was implemented in TSMC 65nm process to demonstrate the feasibility of the architecture. Furthermore, a high dynamic range audio delta sigma modulator using pseudo-pseudo differential topology was investigated and feasibility simulated using TSMC 65nm process. In addition, various novel systems and circuit techniques including efficient calibration of feedback digital to analog converters, new boosted switch and push-pull source follower circuits were investigated to improve upon existing circuit topologies

Concepts for smart AD and DA converters

This thesis studies the `smart' concept for application to analog-to-digital and digital-to-analog converters. The smart concept aims at improving performance - in a wide sense - of AD/DA converters by adding on-chip intelligence to extract imperfections and to correct for them. As the smart concept can correct for certain imperfections, it can also enable the use of more efficient architectures, thus yielding an additional performance boost. Chapter 2 studies trends and expectations in converter design with respect to applications, circuit design and technology evolution. Problems and opportunities are identfied, and an overview of performance criteria is given. Chapter 3 introduces the smart concept that takes advantage of the expected opportunities (described in chapter 2) in order to solve the anticipated problems. Chapter 4 applies the smart concept to digital-to-analog converters. In the discussed example, the concept is applied to reduce the area of the analog core of a current-steering DAC. It is shown that a sub-binary variable-radix approach reduces the area of the current-source elements substantially (10x compared to state-of-the-art), while maintaining accuracy by a self-measurement and digital pre-correction scheme. Chapter 5 describes the chip implementation of the sub-binary variable-radix DAC and discusses the experimental results. The results confirm that the sub-binary variable-radix design can achieve the smallest published current-source-array area for the given accuracy (12bit). Chapter 6 applies the smart concept to analog-to-digital converters, with as main goal the improvement of the overall performance in terms of a widely used figure-of-merit. Open-loop circuitry and time interleaving are shown to be key to achieve high-speed low-power solutions. It is suggested to apply a smart approach to reduce the effect of the imperfections, unintentionally caused by these key factors. On high-level, a global picture of the smart solution is proposed that can solve the problems while still maintaining power-efficiency. Chapter 7 deals with the design of a 500MSps open-loop track-and-hold circuit. This circuit is used as a test case to demonstrate the proposed smart approaches. Experimental results are presented and compared against prior art. Though there are several limitations in the design and the measurement setup, the measured performance is comparable to existing state-of-the-art. Chapter 8 introduces the first calibration method that counteracts the accuracy issues of the open-loop track-and-hold. A description of the method is given, and the implementation of the detection algorithm and correction circuitry is discussed. The chapter concludes with experimental measurement results. Chapter 9 introduces the second calibration method that targets the accuracy issues of time-interleaved circuits, in this case a 2-channel version of the implemented track-and-hold. The detection method, processing algorithm and correction circuitry are analyzed and their implementation is explained. Experimental results verify the usefulness of the method

Energy Efficient and Error Resilient Neuromorphic Computing in VLSI

Realization of the conventional Von Neumann architecture faces increasing challenges due to growing process variations, device reliability and power consumption. As an appealing architectural solution, brain-inspired neuromorphic computing has drawn a great deal of research interest due to its potential improved scalability and power efficiency, and better suitability in processing complex tasks. Moreover, inherit error resilience in neuromorphic computing allows remarkable power and energy savings by exploiting approximate computing. This dissertation focuses on a scalable and energy efficient neurocomputing architecture which leverages emerging memristor nanodevices and a novel approximate arithmetic for cognitive computing. First, brain-inspired digital neuromorphic processor (DNP) architecture with memristive synaptic crossbar is presented for large scale spiking neural networks. We leverage memristor nanodevices to build an N ×N crossbar array to store not only multibit synaptic weight values but also the network configuration data with significantly reduced area cost. Additionally, the crossbar array is accessible both column- and row-wise to significantly expedite the synaptic weight update process for on-chip learning. The proposed digital pulse width modulator (PWM) readily creates a binary pulse with various durations to read and write the multilevel memristors with low cost. Our design integrates N digital leaky integrate-and-fire (LIF) silicon neurons to mimic their biological counterparts and the respective on-chip learning circuits for implementing spike timing dependent plasticity (STDP) learning rules. The proposed column based analog-to-digital conversion (ADC) scheme accumulates the pre-synaptic weights of a neuron efficiently and reduces silicon area by using only one shared arithmetic unit for processing LIF operations of all N neurons. With 256 silicon neurons, the learning circuits and 64K synapses, the power dissipation and area of our design are evaluated as 6.45 mW and 1.86 mm2, respectively, in a 90 nm CMOS technology. Furthermore, arithmetic computations contribute significantly to the overall processing time and power of the proposed architecture. In particular, addition and comparison operations represent 88.5% and 42.9% of processing time and power for digital LIF computation, respectively. Hence, by exploiting the built-in resilience of the presented neuromorphic architecture, we propose novel approximate adder and comparator designs to significantly reduce energy consumption with a very low er- ror rate. The significantly improved error rate and critical path delay stem from a novel carry prediction technique that leverages the information from less significant input bits in a parallel manner. An error magnitude reduction scheme is proposed to further reduce amount of error once detected with low cost in the proposed adder design. Implemented in a commercial 90 nm CMOS process, it is shown that the proposed adder is up to 2.4× faster and 43% more energy efficient over traditional adders while having an error rate of only 0.18%. Additionally, the proposed com- parator achieves an error rate of less than 0.1% and an energy reduction of up to 4.9× compared to the conventional ones. The proposed arithmetic has been adopted in a VLSI-based neuromorphic character recognition chip using unsupervised learning. The approximation errors of the proposed arithmetic units have been shown to have negligible impacts on the training process. Moreover, the energy saving of up to 66.5% over traditional arithmetic units is achieved for the neuromorphic chip with scaled supply levels