Design and debugging of multi-step analog to digital converters

With the fast advancement of CMOS fabrication technology, more and more signal-processing functions are implemented in the digital domain for a lower cost, lower power consumption, higher yield, and higher re-configurability. The trend of increasing integration level for integrated circuits has forced the A/D converter interface to reside on the same silicon in complex mixed-signal ICs containing mostly digital blocks for DSP and control. However, specifications of the converters in various applications emphasize high dynamic range and low spurious spectral performance. It is nontrivial to achieve this level of linearity in a monolithic environment where post-fabrication component trimming or calibration is cumbersome to implement for certain applications or/and for cost and manufacturability reasons. Additionally, as CMOS integrated circuits are accomplishing unprecedented integration levels, potential problems associated with device scaling – the short-channel effects – are also looming large as technology strides into the deep-submicron regime. The A/D conversion process involves sampling the applied analog input signal and quantizing it to its digital representation by comparing it to reference voltages before further signal processing in subsequent digital systems. Depending on how these functions are combined, different A/D converter architectures can be implemented with different requirements on each function. Practical realizations show the trend that to a first order, converter power is directly proportional to sampling rate. However, power dissipation required becomes nonlinear as the speed capabilities of a process technology are pushed to the limit. Pipeline and two-step/multi-step converters tend to be the most efficient at achieving a given resolution and sampling rate specification. This thesis is in a sense unique work as it covers the whole spectrum of design, test, debugging and calibration of multi-step A/D converters; it incorporates development of circuit techniques and algorithms to enhance the resolution and attainable sample rate of an A/D converter and to enhance testing and debugging potential to detect errors dynamically, to isolate and confine faults, and to recover and compensate for the errors continuously. The power proficiency for high resolution of multi-step converter by combining parallelism and calibration and exploiting low-voltage circuit techniques is demonstrated with a 1.8 V, 12-bit, 80 MS/s, 100 mW analog to-digital converter fabricated in five-metal layers 0.18-µm CMOS process. Lower power supply voltages significantly reduce noise margins and increase variations in process, device and design parameters. Consequently, it is steadily more difficult to control the fabrication process precisely enough to maintain uniformity. Microscopic particles present in the manufacturing environment and slight variations in the parameters of manufacturing steps can all lead to the geometrical and electrical properties of an IC to deviate from those generated at the end of the design process. Those defects can cause various types of malfunctioning, depending on the IC topology and the nature of the defect. To relive the burden placed on IC design and manufacturing originated with ever-increasing costs associated with testing and debugging of complex mixed-signal electronic systems, several circuit techniques and algorithms are developed and incorporated in proposed ATPG, DfT and BIST methodologies. Process variation cannot be solved by improving manufacturing tolerances; variability must be reduced by new device technology or managed by design in order for scaling to continue. Similarly, within-die performance variation also imposes new challenges for test methods. With the use of dedicated sensors, which exploit knowledge of the circuit structure and the specific defect mechanisms, the method described in this thesis facilitates early and fast identification of excessive process parameter variation effects. The expectation-maximization algorithm makes the estimation problem more tractable and also yields good estimates of the parameters for small sample sizes. To allow the test guidance with the information obtained through monitoring process variations implemented adjusted support vector machine classifier simultaneously minimize the empirical classification error and maximize the geometric margin. On a positive note, the use of digital enhancing calibration techniques reduces the need for expensive technologies with special fabrication steps. Indeed, the extra cost of digital processing is normally affordable as the use of submicron mixed signal technologies allows for efficient usage of silicon area even for relatively complex algorithms. Employed adaptive filtering algorithm for error estimation offers the small number of operations per iteration and does not require correlation function calculation nor matrix inversions. The presented foreground calibration algorithm does not need any dedicated test signal and does not require a part of the conversion time. It works continuously and with every signal applied to the A/D converter. The feasibility of the method for on-line and off-line debugging and calibration has been verified by experimental measurements from the silicon prototype fabricated in standard single poly, six metal 0.09-µm CMOS process

Utilizing digital design techniques and circuits to improve energy and design efficiency of analog and mixed-signal circuits

Technology scaling has long driven large growth in the electronics market. With each successive technology generation, digital circuits become more power and area efficient. The large performance increases realized for digital circuits due to digital scaling have not translated to similar performance improvements for analog circuits. First, noise-limited analog circuits are not capable of leveraging the reduced parasitics of advanced processes, since capacitor sizes are generally set by noise requirements. Second, analog circuit performance is closely tied to the achievable device intrinsic gain, which degrades as process sizes shrink. Reduced supply voltages further exacerbate this issue, as the achievable gain per stage is limited by the number of devices that can be stacked while maintaining all devices in saturation. Finally, process variation increases with decreased feature sizes, so analog circuits have deal with increased mismatch and wider variations in threshold voltages, increasing the time required to design a circuit that is robust across process, voltage, and temperature (PVT) variation. This work seeks to address the limitations of analog circuits in advanced technologies by leveraging digital techniques and digital-like circuits that offer improved scalability. The first half of this dissertation investigates replacing the traditional closed-loop residue amplifier in a pipeline analog-to-digital converter (ADC) with an open loop dynamic amplifier. Previous works incorporating dynamic amplifiers have struggled to achieve large gains and have suffered from offset mismatch between the comparator and amplifier, which will only get worse in more advanced technologies. We propose the usage of a residue amplifier that combines an integration stage, to ensure low noise operation, with a positive feedback stage, to ensure high gain and high speed operation. By utilizing this topology, the proposed amplifier was the first dynamic amplifier to achieve a high gain of 32. Additionally, the proposed amplifier can reuse existing comparator hardware in the ADC, removing all offset mismatch between comparator and amplifier. Digital calibration techniques were applied to ensure a constant gain across PVT. The next part of this dissertation tries to overcome the scaling challenges for noise-limited ADCs with band-limited input signals. By leveraging digital filtering techniques to generate a prediction of the band-limited signal, the conversion can be limited to a range that is a fraction of the total ADC input range, allowing for significant decreases in reference and comparator power consumption. This work extends previous works by enabling accurate predictions for any band-limited signal characteristic. Previous works only focused on accurate predictions for low-activity signals. Finally, the large compute power enabled by modern technology scaling is leveraged to improve the design efficiency of analog circuits. A new automated circuit sizing tool is proposed that can achieve better performance than manual designs done by experts in a much shorter amount of time. All of these techniques help to alleviate the power and design efficiency limitations caused by technology scaling.Electrical and Computer Engineerin

Design of Highly Efficient Analog-To-Digital Converters

The demand of higher data rates in communication systems is reflected in the constant evolution of communication standards. LTE-A and WiFi 802.11ac promote the use of carrier aggregation to increase the data rate of a wireless receiver. Recent DTV receivers promote the concept of full band capture to avoid the implementation of complex analog operations such as: filtering, equalization, modulation/demodulation, etc. All these operations can be implemented in a robust manner in the digital domain. Analog-to-Digital Converters (ADCs) are located at the heart of such architectures and require to have larger bandwidths and higher dynamic ranges. However, at higher data rates the power efficiency of ADCs tends to degrade. Moreover, while the scale of channel length in CMOS devices directly benefits the power, speed and area of digital circuits, analog circuits suffer from lower intrinsic gain and higher device mismatch. Thus, it has been difficult to design high-speed ADCs with low-power operation using traditional architectures without relying on increasingly complex digital calibration algorithms. This research presents three ADCs that introduce novel architectures to relax the specifications of the analog circuits and reduce the complexity of the digital calibration algorithms. A low-pass sigma delta ADC with 15 MHz of bandwidth is introduced. The system uses a low-power 7-bit quantizer from which the four most significant bits are used for the operation of the sigma delta ADC. The remaining three least significant bits are used for the realization of a frequency domain algorithm for quantization noise improvement. The prototype was implemented in 130 nm CMOS technology. For this prototype, the use of the 7-bit quantizer and algorithm improved the SNDR from 69 dB to 75 dB. The obtained FoM was 145 fJ/conversion-step. In a second project, the problem of high power consumption demanded from closed loop operational amplifiers operating at Giga hertz frequency is addressed. Especially the dependency of the power consumption to the closed loop gain. This project presents a low-pass sigma delta ADC with 75 MHz bandwidth. The traditional summing amplifier used for excess loop compensation delay is substituted by a summing amplifier with current buffer that decouples the power consumption dependency with the closed loop gain. The prototype was designed in 40 nm CMOS technology achieving 64.9 dB peak SNDR. The operating frequency was 3.2 GHz, the total power consumption was 22 mW and FoM of 106 fJ/conversion-step. In a third project, the same approach of decoupling the power consumption requirements from the closed loop gain is applied to a pipelined ADC. The traditional capacitive multiplying DAC used in the residual amplifier is substituted by a current mode DAC and a transimpedance amplifier. The prototype was implemented in 40 nm CMOS technology achieving 58 dB peak SNDR and 76 dB SFDR with 200 MHz sampling frequency. The ADC consumes 8.4 mW with a FoM of 64 fJ/Conversion-step

Circuits and algorithms for pipelined ADCs in scaled CMOS technologies

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.MIT Barker Engineering Library copy: printed in pages.Also issued printed in pages.Includes bibliographical references (leaves 179-184).CMOS technology scaling is creating significant issues for analog circuit design. For example, reduced signal swing and device gain make it increasingly difficult to realize high-speed, high-gain feedback loops traditionally used in switched capacitor circuits. This research involves two complementary methods for addressing scaling issues. First is the development of two blind digital calibration techniques. Decision Boundary Gap Estimation (DBGE) removes static non-linearities and Chopper Offset Estimation (COE) nulls offsets in pipelined ADCs. Second is the development of circuits for a new architecture called zero-crossing based circuits (ZCBC) that is more amenable to scaling trends. To demonstrate these circuits and algorithms, two different ADCs were designed: an 8 bit, 200MS/s in TSMC 180nm technology, and a 12 bit, 50 MS/s in IBM 90nm technology. Together these techniques can be enabling technologies for both pipelined ADCs and general mixed signal design in deep sub-micron technologies.by Lane Gearle Brooks.Ph.D

Integrated Circuits and Systems for Smart Sensory Applications

Connected intelligent sensing reshapes our society by empowering people with increasing new ways of mutual interactions. As integration technologies keep their scaling roadmap, the horizon of sensory applications is rapidly widening, thanks to myriad light-weight low-power or, in same cases even self-powered, smart devices with high-connectivity capabilities. CMOS integrated circuits technology is the best candidate to supply the required smartness and to pioneer these emerging sensory systems. As a result, new challenges are arising around the design of these integrated circuits and systems for sensory applications in terms of low-power edge computing, power management strategies, low-range wireless communications, integration with sensing devices. In this Special Issue recent advances in application-specific integrated circuits (ASIC) and systems for smart sensory applications in the following five emerging topics: (I) dedicated short-range communications transceivers; (II) digital smart sensors, (III) implantable neural interfaces, (IV) Power Management Strategies in wireless sensor nodes and (V) neuromorphic hardware

Digitally Assisted ADCS.

This work involves the development of digital calibration techniques for Analogto- Digital Converters. According to the 2001 International Technology Roadmap for Semiconductors, improved ADC technology is a key factor in the development of present and future applications. The switched-capacitor (SC) pipeline technique is the most popular method of implementing moderate resolution ADCs. However the advantages of CMOS, which originally made SC circuits feasible, are being eroding by process scaling. Good switches and opamps are becoming increasingly difficult to design and the growing gate leakage of deep submicron MOSFETs is causing difficulty. Traditional ADC schemes do not work well with supply voltages of 1.8V and below. Furthermore, the performance required by present and future wireless and IT applications will not be met by the present day ADC circuits techniques. Bearing in mind the challenges associated with deep sub-micron analog circuitry a new calibration technique for folding ADCs has been developed. Since digital circuitry scales well, this calibration relies heavily on digital techniques. Hence it reduces the amount of analog design involved. As this folding ADC is dominated, in terms of both functionality and power, by digital circuitry, the performance of folding will improve when implemented in smaller geometry processes. An 8-bit, 500MS/s, digitally calibrated folding ADC was designed in TSMC 0.18mm. A second prototype, 9-bit 400MS/s, was designed in ST 90nm. This ADC uses novel folders to reduce thermal noise. The major accomplishments of this work are: · The creation of a new folding ADC architecture that is digitally dominated allowing large transistor mismatch to be tolerated so that small devices can be utilized in the signal path. · The development of modeling techniques, to investigate and analyze the effects of transistor mismatch, folder linearity and redundancy in ADCs. · The design of a new folder circuit topology that decreases the required power consumption for a given noise budget. · The design of a resistor ladder DAC that uses a unique resistor layout to allow any shape ladder to be designed.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/58426/1/ibogue_1.pd

Post Conversion Correction of Non-Linear Mismatches for Time Interleaved Analog-to-Digital Converters

Time Interleaved Analog-to-Digital Converters (TI-ADCs) utilize an architecture which enables conversion rates well beyond the capabilities of a single converter while preserving most or all of the other performance characteristics of the converters on which said architecture is based. Most of the approaches discussed here are independent of architecture; some solutions take advantage of specific architectures. Chapter 1 provides the problem formulation and reviews the errors found in ADCs as well as a brief literature review of available TI-ADC error correction solutions. Chapter 2 presents the methods and materials used in implementation as well as extend the state of the art for post conversion correction. Chapter 3 presents the simulation results of this work and Chapter 4 concludes the work. The contribution of this research is three fold: A new behavioral model was developed in SimulinkTM and MATLABTM to model and test linear and nonlinear mismatch errors emulating the performance data of actual converters. The details of this model are presented as well as the results of cumulant statistical calculations of the mismatch errors which is followed by the detailed explanation and performance evaluation of the extension developed in this research effort. Leading post conversion correction methods are presented and an extension with derivations is presented. It is shown that the data converter subsystem architecture developed is capable of realizing better performance of those currently reported in the literature while having a more efficient implementation

Analog Front-End Circuits for Massive Parallel 3-D Neural Microsystems.

Understanding dynamics of the brain has tremendously improved due to the progress in neural recording techniques over the past five decades. The number of simultaneously recorded channels has actually doubled every 7 years, which implies that a recording system with a few thousand channels should be available in the next two decades. Nonetheless, a leap in the number of simultaneous channels has remained an unmet need due to many limitations, especially in the front-end recording integrated circuits (IC). This research has focused on increasing the number of simultaneously recorded channels and providing modular design approaches to improve the integration and expansion of 3-D recording microsystems. Three analog front-ends (AFE) have been developed using extremely low-power and small-area circuit techniques on both the circuit and system levels. The three prototypes have investigated some critical circuit challenges in power, area, interface, and modularity. The first AFE (16-channels) has optimized energy efficiency using techniques such as moderate inversion, minimized asynchronous interface for data acquisition, power-scalable sampling operation, and a wide configuration range of gain and bandwidth. Circuits in this part were designed in a 0.25μm CMOS process using a 0.9-V single supply and feature a power consumption of 4μW/channel and an energy-area efficiency of 7.51x10^15 in units of J^-1Vrms^-1mm^-2. The second AFE (128-channels) provides the next level of scaling using dc-coupled analog compression techniques to reject the electrode offset and reduce the implementation area further. Signal processing techniques were also explored to transfer some computational power outside the brain. Circuits in this part were designed in a 180nm CMOS process using a 0.5-V single supply and feature a power consumption of 2.5μW/channel, and energy-area efficiency of 30.2x10^15 J^-1Vrms^-1mm^-2. The last AFE (128-channels) shows another leap in neural recording using monolithic integration of recording circuits on the shanks of neural probes. Monolithic integration may be the most effective approach to allow simultaneous recording of more than 1,024 channels. The probe and circuits in this part were designed in a 150 nm SOI CMOS process using a 0.5-V single supply and feature a power consumption of only 1.4μW/channel and energy-area efficiency of 36.4x10^15 J^-1Vrms^-1mm^-2.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/98070/1/ashmouny_1.pd

Electronics for Sensors

The aim of this Special Issue is to explore new advanced solutions in electronic systems and interfaces to be employed in sensors, describing best practices, implementations, and applications. The selected papers in particular concern photomultiplier tubes (PMTs) and silicon photomultipliers (SiPMs) interfaces and applications, techniques for monitoring radiation levels, electronics for biomedical applications, design and applications of time-to-digital converters, interfaces for image sensors, and general-purpose theory and topologies for electronic interfaces

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

Ph.DDOCTOR OF PHILOSOPH