Ultra-low noise, high-frame rate readout design for a 3D-stacked CMOS image sensor

Due to the switch from CCD to CMOS technology, CMOS based image sensors have become smaller, cheaper, faster, and have recently outclassed CCDs in terms of image quality. Apart from the extensive set of applications requiring image sensors, the next technological breakthrough in imaging would be to consolidate and completely shift the conventional CMOS image sensor technology to the 3D-stacked technology. Stacking is recent and an innovative technology in the imaging field, allowing multiple silicon tiers with different functions to be stacked on top of each other. The technology allows for an extreme parallelism of the pixel readout circuitry. Furthermore, the readout is placed underneath the pixel array on a 3D-stacked image sensor, and the parallelism of the readout can remain constant at any spatial resolution of the sensors, allowing extreme low noise and a high-frame rate (design) at virtually any sensor array resolution. The objective of this work is the design of ultra-low noise readout circuits meant for 3D-stacked image sensors, structured with parallel readout circuitries. The readout circuit’s key requirements are low noise, speed, low-area (for higher parallelism), and low power. A CMOS imaging review is presented through a short historical background, followed by the description of the motivation, the research goals, and the work contributions. The fundamentals of CMOS image sensors are addressed, as a part of highlighting the typical image sensor features, the essential building blocks, types of operation, as well as their physical characteristics and their evaluation metrics. Following up on this, the document pays attention to the readout circuit’s noise theory and the column converters theory, to identify possible pitfalls to obtain sub-electron noise imagers. Lastly, the fabricated test CIS device performances are reported along with conjectures and conclusions, ending this thesis with the 3D-stacked subject issues and the future work. A part of the developed research work is located in the Appendices.Devido à mudança da tecnologia CCD para CMOS, os sensores de imagem em CMOS tornam se mais pequenos, mais baratos, mais rápidos, e mais recentemente, ultrapassaram os sensores CCD no que respeita à qualidade de imagem. Para além do vasto conjunto de aplicações que requerem sensores de imagem, o próximo salto tecnológico no ramo dos sensores de imagem é o de mudar completamente da tecnologia de sensores de imagem CMOS convencional para a tecnologia “3D-stacked”. O empilhamento de chips é relativamente recente e é uma tecnologia inovadora no campo dos sensores de imagem, permitindo vários planos de silício com diferentes funções poderem ser empilhados uns sobre os outros. Esta tecnologia permite portanto, um paralelismo extremo na leitura dos sinais vindos da matriz de píxeis. Além disso, num sensor de imagem de planos de silício empilhados, os circuitos de leitura estão posicionados debaixo da matriz de píxeis, sendo que dessa forma, o paralelismo pode manter-se constante para qualquer resolução espacial, permitindo assim atingir um extremo baixo ruído e um alto debito de imagens, virtualmente para qualquer resolução desejada. O objetivo deste trabalho é o de desenhar circuitos de leitura de coluna de muito baixo ruído, planeados para serem empregues em sensores de imagem “3D-stacked” com estruturas altamente paralelizadas. Os requisitos chave para os circuitos de leitura são de baixo ruído, rapidez e pouca área utilizada, de forma a obter-se o melhor rácio. Uma breve revisão histórica dos sensores de imagem CMOS é apresentada, seguida da motivação, dos objetivos e das contribuições feitas. Os fundamentos dos sensores de imagem CMOS são também abordados para expor as suas características, os blocos essenciais, os tipos de operação, assim como as suas características físicas e suas métricas de avaliação. No seguimento disto, especial atenção é dada à teoria subjacente ao ruído inerente dos circuitos de leitura e dos conversores de coluna, servindo para identificar os possíveis aspetos que dificultem atingir a tão desejada performance de muito baixo ruído. Por fim, os resultados experimentais do sensor desenvolvido são apresentados junto com possíveis conjeturas e respetivas conclusões, terminando o documento com o assunto de empilhamento vertical de camadas de silício, junto com o possível trabalho futuro

Digital CMOS ISFET architectures and algorithmic methods for point-of-care diagnostics

Over the past decade, the surge of infectious diseases outbreaks across the globe is redefining how healthcare is provided and delivered to patients, with a clear trend towards distributed diagnosis at the Point-of-Care (PoC). In this context, Ion-Sensitive Field Effect Transistors (ISFETs) fabricated on standard CMOS technology have emerged as a promising solution to achieve a precise, deliverable and inexpensive platform that could be deployed worldwide to provide a rapid diagnosis of infectious diseases. This thesis presents advancements for the future of ISFET-based PoC diagnostic platforms, proposing and implementing a set of hardware and software methodologies to overcome its main challenges and enhance its sensing capabilities. The first part of this thesis focuses on novel hardware architectures that enable direct integration with computational capabilities while providing pixel programmability and adaptability required to overcome pressing challenges on ISFET-based PoC platforms. This section explores oscillator-based ISFET architectures, a set of sensing front-ends that encodes the chemical information on the duty cycle of a PWM signal. Two initial architectures are proposed and fabricated in AMS 0.35um, confirming multiple degrees of programmability and potential for multi-sensing. One of these architectures is optimised to create a dual-sensing pixel capable of sensing both temperature and chemical information on the same spatial point while modulating this information simultaneously on a single waveform. This dual-sensing capability, verified in silico using TSMC 0.18um process, is vital for DNA-based diagnosis where protocols such as LAMP or PCR require precise thermal control. The COVID-19 pandemic highlighted the need for a deliverable diagnosis that perform nucleic acid amplification tests at the PoC, requiring minimal footprint by integrating sensing and computational capabilities. In response to this challenge, a paradigm shift is proposed, advocating for integrating all elements of the portable diagnostic platform under a single piece of silicon, realising a ``Diagnosis-on-a-Chip". This approach is enabled by a novel Digital ISFET Pixel that integrates both ADC and memory with sensing elements on each pixel, enhancing its parallelism. Furthermore, this architecture removes the need for external instrumentation or memories and facilitates its integration with computational capabilities on-chip, such as the proposed ARM Cortex M3 system. These computational capabilities need to be complemented with software methods that enable sensing enhancement and new applications using ISFET arrays. The second part of this thesis is devoted to these methods. Leveraging the programmability capabilities available on oscillator-based architectures, various digital signal processing algorithms are implemented to overcome the most urgent ISFET non-idealities, such as trapped charge, drift and chemical noise. These methods enable fast trapped charge cancellation and enhanced dynamic range through real-time drift compensation, achieving over 36 hours of continuous monitoring without pixel saturation. Furthermore, the recent development of data-driven models and software methods open a wide range of opportunities for ISFET sensing and beyond. In the last section of this thesis, two examples of these opportunities are explored: the optimisation of image compression algorithms on chemical images generated by an ultra-high frame-rate ISFET array; and a proposed paradigm shift on surface Electromyography (sEMG) signals, moving from data-harvesting to information-focused sensing. These examples represent an initial step forward on a journey towards a new generation of miniaturised, precise and efficient sensors for PoC diagnostics.Open Acces

Ultra-Low Power IoT Smart Visual Sensing Devices for Always-ON Applications

This work presents the design of a Smart Ultra-Low Power visual sensor architecture that couples together an ultra-low power event-based image sensor with a parallel and power-optimized digital architecture for data processing. By means of mixed-signal circuits, the imager generates a stream of address events after the extraction and binarization of spatial gradients. When targeting monitoring applications, the sensing and processing energy costs can be reduced by two orders of magnitude thanks to either the mixed-signal imaging technology, the event-based data compression and the use of event-driven computing approaches. From a system-level point of view, a context-aware power management scheme is enabled by means of a power-optimized sensor peripheral block, that requests the processor activation only when a relevant information is detected within the focal plane of the imager. When targeting a smart visual node for triggering purpose, the event-driven approach brings a 10x power reduction with respect to other presented visual systems, while leading to comparable results in terms of detection accuracy. To further enhance the recognition capabilities of the smart camera system, this work introduces the concept of event-based binarized neural networks. By coupling together the theory of binarized neural networks and focal-plane processing, a 17.8% energy reduction is demonstrated on a real-world data classification with a performance drop of 3% with respect to a baseline system featuring commercial visual sensors and a Binary Neural Network engine. Moreover, if coupling the BNN engine with the event-driven triggering detection flow, the average power consumption can be as low as the sleep power of 0.3mW in case of infrequent events, which is 8x lower than a smart camera system featuring a commercial RGB imager

Flexi-WVSNP-DASH: A Wireless Video Sensor Network Platform for the Internet of Things

abstract: Video capture, storage, and distribution in wireless video sensor networks (WVSNs) critically depends on the resources of the nodes forming the sensor networks. In the era of big data, Internet of Things (IoT), and distributed demand and solutions, there is a need for multi-dimensional data to be part of the Sensor Network data that is easily accessible and consumable by humanity as well as machinery. Images and video are expected to become as ubiquitous as is the scalar data in traditional sensor networks. The inception of video-streaming over the Internet, heralded a relentless research for effective ways of distributing video in a scalable and cost effective way. There has been novel implementation attempts across several network layers. Due to the inherent complications of backward compatibility and need for standardization across network layers, there has been a refocused attention to address most of the video distribution over the application layer. As a result, a few video streaming solutions over the Hypertext Transfer Protocol (HTTP) have been proposed. Most notable are Apple’s HTTP Live Streaming (HLS) and the Motion Picture Experts Groups Dynamic Adaptive Streaming over HTTP (MPEG-DASH). These frameworks, do not address the typical and future WVSN use cases. A highly flexible Wireless Video Sensor Network Platform and compatible DASH (WVSNP-DASH) are introduced. The platform's goal is to usher video as a data element that can be integrated into traditional and non-Internet networks. A low cost, scalable node is built from the ground up to be fully compatible with the Internet of Things Machine to Machine (M2M) concept, as well as the ability to be easily re-targeted to new applications in a short time. Flexi-WVSNP design includes a multi-radio node, a middle-ware for sensor operation and communication, a cross platform client facing data retriever/player framework, scalable security as well as a cohesive but decoupled hardware and software design.Dissertation/ThesisDoctoral Dissertation Electrical Engineering 201

Development of electronics for microultrasound capsule endoscopy

Development of intracorporeal devices has surged in the last decade due to advancements in the semiconductor industry, energy storage and low-power sensing systems. This work aims to present a thorough systematic overview and exploration of the microultrasound (µUS) capsule endoscopy (CE) field as the development of electronic components will be key to a successful applicable µUSCE device. The research focused on investigating and designing high-voltage (HV, < 36 V) generating and driving circuits as well as a low-noise amplifier (LNA) for battery-powered and volume-limited systems. In implantable applications, HV generation with maximum efficiency is required to improve the operational lifetime whilst reducing the cost of the device. A fully integrated hybrid (H) charge pump (CP) comprising a serial-parallel (SP) stage was designed and manufactured for > 20 V and 0 - 100 µA output capabilities. The results were compared to a Dickson (DKCP) occupying the same chip area; further improvements in the SPCP topology were explored and a new switching scheme for SPCPs was introduced. A second regulated CP version was excogitated and manufactured to use with an integrated µUS pulse generator. The CP was manufactured and tested at different output currents and capacitive loads; its operation with an US pulser was evaluated and a novel self-oscillating CP mechanism to eliminate the need of an auxiliary clock generator with a minimum area overhead was devised. A single-output universal US pulser was designed, manufactured and tested with 1.5 MHz, 3 MHz, and 28 MHz arrays to achieve a means of fully-integrated, low-power transducer driving. The circuit was evaluated for power consumption and pulse generation capabilities with different loads. Pulse-echo measurements were carried out and compared with those from a commercial US research system to characterise and understand the quality of the generated pulse. A second pulser version for a 28 MHz array was derived to allow control of individual elements. The work involved its optimisation methodology and design of a novel HV feedback-based level-shifter. A low-noise amplifier (LNA) was designed for a wide bandwidth µUS array with a centre frequency of 28 MHz. The LNA was based on an energy-efficient inverter architecture. The circuit encompassed a full power-down functionality and was investigated for a self-biased operation to achieve lower chip area. The explored concepts enable realisation of low power and high performance LNAs for µUS frequencies

Leveraging Eye Structure and Motion to Build a Low-Power Wearable Gaze Tracking System

Clinical studies have shown that features of a person\u27s eyes can function as an effective proxy for cognitive state and neurological function. Technological advances in recent decades have allowed us to deepen this understanding and discover that the actions of the eyes are in fact very tightly coupled to the operation of the brain. Researchers have used camera-based eye monitoring technology to exploit this connection and analyze mental state across across many different metrics of interest. These range from simple things like attention and scene processing, to impairments such as a fatigue or substance use, and even significant mental disorders such as Parkinson\u27s, autism, and schizophrenia. While there is a wealth of knowledge and social benefit to be gained from eye tracking, the field has historically been restricted to laboratory use by crippling technological limitations - most notably, device size and power consumption. These issues primarily stem from the use of high-resolution cameras and heavyweight video-processing algorithms, both of which induce extremely high performance overhead on the eye tracker. To address this problem, we have constructed a lightweight, ultra-low-power eye monitoring device in the form factor of a pair of eyeglasses. The key guiding design principle for its construction was saliency-aware resource minimization. Specifically, our design leverages the fact that close-up images of the eye are characterized by large salient features which provide a high degree of redundant information; we exploit this to heavily subsample the eye image and reduce resource utilization while performing effective eye tracking. In the first part of this thesis, we present an initial design of a wearable system to enable ubiquitous eye tracking. By exploiting the fact that the eye has several large, visually redundant features such as the iris and pupil, we were able to develop a neural-network-based adaptive-sampling algorithm for predicting the gaze point while sampling a minimal number of pixels from the image. This enabled us to realize a power savings using specialized imaging hardware that would sample only those most salient pixels, which proportionally reduced the power and time cost of reading images for eye tracking. With these optimizations we were able to build a first-of-of its kind wearable eye tracker that consumed 40 mW of power and demonstrated a gaze tracking error of only 3 degrees across multiple subjects. We refer to this device as the iShadow platform. The second contribution and section of this thesis is a significant improvement upon the original iShadow design for the purpose of improving both power utilization and eye tracking performance. We constructed a new pupil-tracking algorithm based on lightweight computer vision features, which leverages the smoothness of the eye\u27s motion to reduce even further the amount of camera sampling needed. To guard against very infrequent discontinuities resulting from blinks or reflections off the eye, we integrated this model with the previously-used one-shot neural network algorithm. Because the common case (smooth, uninterrupted eye motion) occurs 90% of the time, we were able to realize a dramatic increase in performance due to the efficiency of the smooth tracking algorithm. The new and improved system, labeled CIDER, enabled much more accurate eye tracking - 0.4 degree error - with power consumption as low as 7 mW. This design also enabled a tradeoff between power consumption and eye tracking rate, in which it was also possible to draw higher power of ~30 mW in order to do eye tracking at rates of up to 240 frames per second. The final contribution of this thesis is a re-designed version of the iShadow glasses hardware that is suitable for ``in-the-wild\u27\u27 studies on subjects in their daily living environment. A wearable device, especially one that is worn on the head, must be minimally obtrusive in order to be accepted and used in the field by subjects. This design goal conflicts with the ideal placement of cameras that is needed for achieving consistent eye tracking fidelity. We present multiple possible methods we explored for addressing these competing design challenges, and discuss the reasons that many proved infeasible. To conclude, we present a working design solution that appears to optimally trade off user comfort and convenience and against the technical requirements of the system

Concepts for Short Range Millimeter-wave Miniaturized Radar Systems with Built-in Self-Test

This work explores short-range millimeter wave radar systems, with emphasis on miniaturization and overall system cost reduction. The designing and implementation processes, starting from the system level design considerations and characterization of the individual components to final implementation of the proposed architecture are described briefly. Several D-band radar systems are developed and their functionality and performances are demonstrated

Heterogeneous Chip Multiprocessor: Data Representation, Mixed-Signal Processing Tiles, and System Design

With the emergence of big data, the need for more computationally intensive processors that can handle the increased processing demand has risen. Conventional computing paradigms based on the Von Neumann model that separates computational and memory structures have become outdated and less efficient for this increased demand. As the speed and memory density of processors have increased significantly over the years, these models of computing, which rely on a constant stream of data between the processor and memory, see less gains due to finite bandwidth and latency. Moreover, in the presence of extreme scaling, these conventional systems, implemented in submicron integrated circuits, have become even more susceptible to process variability, static leakage current, and more. In this work, alternative paradigms, predicated on distributive processing with robust data representation and mixed-signal processing tiles, are explored for constructing more efficient and scalable computing systems in application specific integrated circuits (ASICs). The focus of this dissertation work has been on heterogeneous chip multi-processor (CMP) design and optimization across different levels of abstraction. On the level of data representation, a different modality of representation based on random pulse density modulation (RPDM) coding is explored for more efficient processing using stochastic computation. On the level of circuit description, mixed-signal integrated circuits that exploit charge-based computing for energy efficient fixed point arithmetic are designed. Consequently, 8 different chips that test and showcase these circuits were fabricated in submicron CMOS processes. Finally, on the architectural level of description, a compact instruction-set processor and controller that facilitates distributive computing on System-On-Chips (SoCs) is designed. In addition to this, a robust bufferless network architecture is designed with a network simulator, and I/O cells are designed for SoCs. The culmination of this thesis work has led to the design and fabrication of a heterogeneous chip multi- processor prototype comprised of over 12,000 VVM cores, warp/dewarp processors, cache, and additional processors, which can be applied towards energy efficient large-scale data processing

Design automation and analysis of three-dimensional integrated circuits

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.Includes bibliographical references (p. 165-176).This dissertation concerns the design of circuits and systems for an emerging technology known as three-dimensional integration. By stacking individual components, dice, or whole wafers using a high-density electromechanical interconnect, three-dimensional integration can achieve scalability and performance exceeding that of conventional fabrication technologies. There are two main contributions of this thesis. The first is a computer-aided design flow for the digital components of a three-dimensional integrated circuit (3-D IC). This flow primarily consists of two software tools: PR3D, a placement and routing tool for custom 3-D ICs based on standard cells, and 3-D Magic, a tool for designing, editing, and testing physical layout characteristics of 3-D ICs. The second contribution of this thesis is a performance analysis of the digital components of 3-D ICs. We use the above tools to determine the extent to which 3-D integration can improve timing, energy, and thermal performance. In doing so, we verify the estimates of stochastic computational models for 3-D IC interconnects and find that the models predict the optimal 3-D wire length to within 20% accuracy. We expand upon this analysis by examining how 3-D technology factors affect the optimal wire length that can be obtained. Our ultimate analysis extends this work by directly considering timing and energy in 3-D ICs. In all cases we find that significant performance improvements are possible. In contrast, thermal performance is expected to worsen with the use of 3-D integration. We examine precisely how thermal behavior scales in 3-D integration and determine quantitatively how the temperature may be controlled during the circuit placement process. We also show how advanced packaging(cont.) technologies may be leveraged to maintain acceptable die temperatures in 3-D ICs. Finally, we explore two issues for the future of 3-D integration. We determine how technology scaling impacts the effect of 3-D integration on circuit performance. We also consider how to improve the performance of digital components in a mixed-signal 3-D integrated circuit. We conclude with a look towards future 3-D IC design tools.by Shamik Das.Ph.D

Injection locked ring oscillator design for application in Direct Time of Flight LIDAR

Diplomová práce přibližuje systémy LIDAR přímo měřící čas průletu a časově digitální převodníky určené k použití v těchto systémech. Představuje problematiku distribuce hodinových signálů napříč soubory časově digitálních převodníků v LIDAR systémech a věnuje se jednomu z nových řešení této problematiky, které je založené na injekcí zavěšených oscilátorech. Technika injekčního zavěšení oscilátorů je důkladně matematicky popsána. V programu Matlab byl vytvořen simulační model injekcí zavěšeného kruhového oscilátoru, který potvrzuje správnost uvedených analytických predikcí. Ve výrobní technologii ONK65 byl navržen injekcí zavěšený kruhový oscilátor stabilizovaný pomocí smyčky závěsu zpoždění, určený pro implementaci časově digitálního převodníku pro systém LIDAR. Navržený injekcí zavěšený kruhový oscilátor byl verifikován počítačovými simulacemi zohledňujícími vliv procesních, napěťových i teplotních variací. Oscilátor poskytuje specifikované časové rozlišení 50 pikosekund a dosahuje dvakrát nižší hodnoty fázového neklidu než ekvivalentní volnoběžný oscilátor v dané technologii.The diploma thesis provides an introduction to Direct Time of Flight LIDAR systems and Time to Digital Converters used in these systems. It discusses the problem of clock distribution in LIDAR Time to Digital Converter arrays, and examines one of the possible solutions to this problem based on injection locked oscillators. The injection locking phenomenon is thoroughly mathematically described and a Matlab model of an injection locked ring oscillator is presented, confirming the analytic predictions. In ONK65 processing technology, an injection locked ring oscillator biased by a delay locked loop meant specifically for application in Time to Digital Converters for LIDAR systems has been designed. The designed oscillator has been verified by computer simulations taking process, voltage and temperature variations into account and offers specified time resolution of 50 picosecond as well as two times less clock jitter than an equivalent free-running oscillator in the given processing technology.