21 research outputs found
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A 90.5dB DR 1MHz BW Hybrid Two Step ADC with CT Incremental and SAR ADCs
The sensors in real time data processing IoT devices require high resolution and sub-MHz data converters, usually implemented as Incremental ADCs due to the advantages of oversampling technique and low latency. In discrete time incremental (IDT) ADCs, the sampling switch non-linearity, charge injection degrade the resolution, and power hungry OPAMPs are demanded to provide fast and accurate settling for the switch-capacitor circuits. While the continuous time incremental (ICT) ADCs overcome these issues by removing the sampling switches and it also relax the OPAMPs settling accuracy to save power. A hybrid architecture of ICT ADC and SAR two step ADC is proposed to achieve high resolution at low oversampling ratio (OSR). The first ICT ADCs enable higher resolution, faster conversion speed with lower power consumption. The residual error of the ICT ADC is extracted at the last integrator output and transfers to the 2nd SAR for further conversion. In this architecture, only the mismatch between the cascade of integrators (CoIs) and decimation filter transfer functions causes 1st stage quantization noise leakage which can be solved by increasing opamp parameters instead of increasing the digital decimation filter complexity. In addition, the overall SQNR is independent of the first ICT ADC’s NTF, which gives more freedom to trade-off between the loop stability and DAC errors. A 4bits DRZ DAC with data weighted averaging (DWA) technique is adopted to reduce the clock jitter of DAC, mitigate ISI error and static mismatch errors. Based on this architecture, a 16b resolution, 1MHz signal bandwidth hybrid two step ADC is designed and measurement results are demonstrated. Important sub circuits are introduced and analyzed in detail to get the target resolution. The ADC is fabricated in AKM 180nm CMOS process with 1.8V supply voltage, it achieves a DR of 90.5dB, and SNR/SFDR/SNDR of 82.5dB/85dB/80.5dB over 1MHz BW sampled at 64MHz
Extended-Range Second-Order Incremental Sigma-Delta ADC
A single-stage two-steps Extended-Range Second-Order Incremental ADC in 0.13um CMOS technology is presented here which achieves a Signal-to-Noise and Distortion Ratio (SNDR) as large as 73 dB. The proposed architecture of Extended-Range ADC based on Second-order multi-bit CIFF Incremental ADC reuses the IADC structure for coarse (input signal) as well as fine (residue) quantization without need of employment of explicit second ADC thereby minimizing power consumption and area occupancy. With a clock frequency of 80 MHz, the complete ERADC achieves in extracted simulation a peak SNDR of 73 dB at a data rate of 3.2 MS/s (25 clock cycles per conversion).A single-stage two-steps Extended-Range Second-Order Incremental ADC in 0.13um CMOS technology is presented here which achieves a Signal-to-Noise and Distortion Ratio (SNDR) as large as 73 dB. The proposed architecture of Extended-Range ADC based on Second-order multi-bit CIFF Incremental ADC reuses the IADC structure for coarse (input signal) as well as fine (residue) quantization without need of employment of explicit second ADC thereby minimizing power consumption and area occupancy. With a clock frequency of 80 MHz, the complete ERADC achieves in extracted simulation a peak SNDR of 73 dB at a data rate of 3.2 MS/s (25 clock cycles per conversion)
Architectural Alternatives to Implement High-Performance Delta-Sigma Modulators
RÉSUMÉ Le besoin d’appareils portatifs, de téléphones intelligents et de systèmes microélectroniques implantables médicaux s’accroît remarquablement. Cependant, l’optimisation de l’alimentation de tous ces appareils électroniques portables est l’un des principaux défis en raison du manque de piles à grande capacité utilisées pour les alimenter. C’est un fait bien établi que le convertisseur analogique-numérique (CAN) est l’un des blocs les plus critiques de ces appareils et qu’il doit convertir efficacement les signaux analogiques au monde numérique pour effectuer un post-traitement tel que l’extraction de caractéristiques. Parmi les différents types de CAN, les modulateurs Delta Sigma (��M) ont été utilisés dans ces appareils en raison des fonctionnalités alléchantes qu’ils offrent. En raison du suréchantillonnage et pour éloigner le bruit de la bande d’intérêt, un CAN haute résolution peut être obtenu avec les architectures ��. Il offre également un compromis entre la fréquence d’échantillonnage et la résolution, tout en offrant une architecture programmable pour réaliser un CAN flexible. Ces CAN peuvent être implémentés avec des blocs analogiques de faible précision. De plus, ils peuvent être efficacement optimisés au niveau de l’architecture et circuits correspondants. Cette dernière caractéristique a été une motivation pour proposer différentes architectures au fil des ans. Cette thèse contribue à ce sujet en explorant de nouvelles architectures pour optimiser la structure ��M en termes de résolution, de consommation d’énergie et de surface de silicium. Des soucis particuliers doivent également être pris en compte pour faciliter la mise en œuvre du ��M. D’autre part, les nouveaux procédés CMOS de conception et fabrication apportent des améliorations remarquables en termes de vitesse, de taille et de consommation d’énergie lors de la mise en œuvre de circuits numériques. Une telle mise à l’échelle agressive des procédés, rend la conception de blocs analogiques tel que un amplificateur de transconductance opérationnel (OTA), difficile. Par conséquent, des soins spéciaux sont également pris en compte dans cette thèse pour surmonter les problèmes énumérés. Ayant mentionné ci-dessus que cette thèse est principalement composée de deux parties principales. La première concerne les nouvelles architectures implémentées en mode de tension et la seconde partie contient une nouvelle architecture réalisée en mode hybride tension et temps.----------ABSTRACT The need for hand-held devices, smart-phones and medical implantable microelectronic sys-tems, is remarkably growing up. However, keeping all these electronic devices power optimized is one of the main challenges due to the lack of long life-time batteries utilized to power them up. It is a well-established fact that analog-to-digital converter (ADC) is one of the most critical building blocks of such devices and it needs to efficiently convert analog signals to the digital world to perform post processing such as channelizing, feature extraction, etc. Among various type of ADCs, Delta Sigma Modulators (��Ms) have been widely used in those devices due to the tempting features they offer. In fact, due to oversampling and noise-shaping technique a high-resolution ADC can be achieved with �� architectures. It also offers a compromise between sampling frequency and resolution while providing a highly-programmable approach to realize an ADC. Moreover, such ADCs can be implemented with low-precision analog blocks. Last but not the least, they are capable of being effectively power optimized at both architectural and circuit levels. The latter has been a motivation to proposed different architectures over the years.This thesis contributes to this topic by exploring new architectures to effectively optimize the ��M structure in terms of resolution, power consumption and chip area. Special cares must also be taken into account to ease the implementation of the ��M. On the other hand, advanced node CMOS processes bring remarkable improvements in terms of speed, size and power consumption while implementing digital circuits. Such an aggressive process scaling, however, make the design of analog blocks, e.g. operational transconductance amplifiers (OTAs), cumbersome. Therefore, special cares are also taken into account in this thesis to overcome the mentioned issues. Having had above mentioned discussion, this thesis is mainly split in two main categories. First category addresses new architectures implemented in a pure voltage domain and the second category contains new architecture realized in a hybrid voltage and time domain. In doing so, the thesis first focuses on a switched-capacitor implementation of a ��M while presenting an architectural solution to overcome the limitations of the previous approaches. This limitations include a power hungry adder in a conventional feed-forward topology as well as power hungry OTAs
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
Area- and Energy- Efficient Modular Circuit Architecture for 1,024-Channel Parallel Neural Recording Microsystem.
This research focuses to develop system architectures and associated electronic circuits for a next generation neuroscience research tool, a massive-parallel neural recording system capable of recording 1,024 channels simultaneously. Three interdependent prototypes have been developed to address major challenges in realization of the massive-parallel neural recording microsystems: minimization of energy and area consumption while preserving high quality in recordings.
First, a modular 128-channel Δ-ΔΣ AFE using the spectrum shaping has been designed and fabricated to propose an area-and energy efficient solution for neural recording AFEs. The AFE achieved 4.84 fJ/C−s·mm2 figure of merit that is the smallest the area-energy product among the state-of-the-art multichannel neural recording systems. It also features power and area consumption of 3.05 µW and 0.05 mm2 per channel, respectively while exhibiting 63.3 dB signal-to-noise ratio with 3.02 µVrms input referred noise.
Second, an on-chip mixed signal neural signal compressor was built to reduce the energy consumption in handling and transmission of the recorded data since this occupies a large portion of the total energy consumption as the number of parallel recording increases. The compressor reduces the data rates of two distinct groups of neural signals that are essential for neuroscience research: LFP and AP without loss of informative signals. As a result, the power consumptions for the data handling and transmissions of the LFP and AP were reduced to about 1/5.35 and 1/10.54 of the uncompressed cases, respectively. In the total data handling and transmission, the measured power consumption per channel is 11.98 µW that is about 1/9 of 107.5 µW without the compression.
Third, a compact on-chip dc-to-dc converter with constant 1 MHz switching frequency has been developed to provide reliable power supplies and enhance energy delivery efficiency to the massive-parallel neural recording systems. The dc-to-dc converter has only predictable tones at the output and it exhibits > 80% power conversion efficiency at ultra-light loads, < 100 µW that is relevant power most of the multi-channel neural recording systems consume. The dc-to-dc converter occupies 0.375 mm2 of area which is less than 1/20 of the area the first prototype consumes (8.64 mm2).PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133244/1/sungyun_1.pd
Resource-Constrained Acquisition Circuits for Next Generation Neural Interfaces
The development of neural interfaces allowing the acquisition of signals from the cortex of the brain has seen an increasing amount of interest both in academic research as well as in the commercial space due to their ability to aid people with various medical conditions, such as spinal cord injuries, as well as their potential to allow more seamless interactions between people and machines. While it has already been demonstrated that neural implants can allow tetraplegic patients to control robotic arms, thus to an extent returning some motoric function, the current state of the art often involves the use of heavy table-top instruments connected by wires passing through the patient’s skull, thus making the applications impractical and chronically infeasible.
Those limitations are leading to the development of the next generation of neural interfaces that will overcome those issues by being minimal in size and completely wireless, thus paving a way to the possibility of their chronic application. Their development however faces several challenges in numerous aspects of engineering due to constraints presented by their minimal size, amount of power available as well as the materials that can be utilised.
The aim of this work is to explore some of those challenges and investigate novel circuit techniques that would allow the implementation of acquisition analogue front-ends under the presented constraints. This is facilitated by first giving an overview of the problematic of recording electrodes and their electrical characterisation in terms of their impedance profile and added noise that can be used to guide the design of analogue front-ends.
Continuous time (CT) acquisition is then investigated as a promising signal digitisation technique alternative to more conventional methods in terms of its suitability. This is complemented by a description of practical implementations of a CT analogue-to-digital converter (ADC) including a novel technique of clockless stochastic chopping aimed at the suppression of flicker noise that commonly affects the acquisition of low-frequency signals. A compact design is presented, implementing a 450 nW, 5.5 bit ENOB CT ADC, occupying an area of 0.0288 mm2 in a 0.18 μm CMOS technology, making this the smallest presented design in literature to the best of our knowledge.
As completely wireless neural implants rely on power delivered through wireless links, their supply voltage is often subject to large high frequency variations as well voltage uncertainty making it necessary to design reference circuits and voltage regulators providing stable reference voltage and supply in the constrained space afforded to them. This results in numerous challenges that are explored and a design of a practical implementation of a reference circuit and voltage regulator is presented. Two designs in a 0.35 μm CMOS technology are presented, showing respectively a measured PSRR of ≈60 dB and ≈53 dB at DC and a worst-case PSRR of ≈42 dB and ≈33 dB with a less than 1% standard deviation in the output reference voltage of 1.2 V while consuming a power of ≈7 μW.
Finally, ΣΔ modulators are investigated for their suitability in neural signal acquisition chains, their properties explained and a practical implementation of a ΣΔ DC-coupled neural acquisition circuit presented. This implements a 10-kHz, 40 dB SNDR ΣΔ analogue front-end implemented in a 0.18 μm CMOS technology occupying a compact area of 0.044 μm2 per channel while consuming 31.1 μW per channel.Open Acces
Interface Circuits for Microsensor Integrated Systems
ca. 200 words; this text will present the book in all promotional forms (e.g. flyers). Please describe the book in straightforward and consumer-friendly terms. [Recent advances in sensing technologies, especially those for Microsensor Integrated Systems, have led to several new commercial applications. Among these, low voltage and low power circuit architectures have gained growing attention, being suitable for portable long battery life devices. The aim is to improve the performances of actual interface circuits and systems, both in terms of voltage mode and current mode, in order to overcome the potential problems due to technology scaling and different technology integrations. Related problems, especially those concerning parasitics, lead to a severe interface design attention, especially concerning the analog front-end and novel and smart architecture must be explored and tested, both at simulation and prototype level. Moreover, the growing demand for autonomous systems gets even harder the interface design due to the need of energy-aware cost-effective circuit interfaces integrating, where possible, energy harvesting solutions. The objective of this Special Issue is to explore the potential solutions to overcome actual limitations in sensor interface circuits and systems, especially those for low voltage and low power Microsensor Integrated Systems. The present Special Issue aims to present and highlight the advances and the latest novel and emergent results on this topic, showing best practices, implementations and applications. The Guest Editors invite to submit original research contributions dealing with sensor interfacing related to this specific topic. Additionally, application oriented and review papers are encouraged.