155 research outputs found
Linearization of Time-encoded ADCs Architectures for Smart MEMS Sensors in Low Power CMOS Technology
Mención Internacional en el título de doctorIn the last few years, the development of mobile technologies and machine learning
applications has increased the demand of MEMS-based digital microphones.
Mobile devices have several microphones enabling noise canceling, acoustic beamforming
and speech recognition. With the development of machine learning applications
the interest to integrate sensors with neural networks has increased.
This has driven the interest to develop digital microphones in nanometer CMOS
nodes where the microphone analog-front end and digital processing, potentially
including neural networks, is integrated on the same chip.
Traditionally, analog-to-digital converters (ADCs) in digital microphones have
been implemented using high order Sigma-Delta modulators. The most common
technique to implement these high order Sigma-Selta modulators is switchedcapacitor
CMOS circuits. Recently, to reduce power consumption and make them
more suitable for tasks that require always-on operation, such as keyword recognition,
switched-capacitor circuits have been improved using inverter-based operational
amplifier integrators. Alternatively, switched-capacitor based Sigma-
Delta modulators have been replaced by continuous time Sigma-Delta converters.
Nevertheless, in both implementations the input signal is voltage encoded
across the modulator, making the integration in smaller CMOS nodes more challenging
due to the reduced voltage supply.
An alternative technique consists on encoding the input signal on time (or
frequency) instead of voltage. This is what time-encoded converters do. Lately,
time-encoding converters have gained popularity as they are more suitable to
nanometer CMOS nodes than Sigma-Delta converters. Among the ones that have
drawn more interest we find voltage-controlled oscillator based ADCs (VCOADCs).
VCO-ADCs can be implemented using CMOS inverter based ring oscillators
(RO) and digital circuitry. They also show noise-shaping properties.
This makes them a very interesting alternative for implementation of ADCs in
nanometer CMOS nodes. Nevertheless, two main circuit impairments are present
in VCO-ADCs, and both come from the oscillator non-idealities. The first of them
is the oscillator phase noise, that reduces the resolution of the ADC. The second
is the non-linear tuning curve of the oscillator, that results in harmonic distortion
at medium to high input amplitudes.
In this thesis we analyze the use of time encoding ADCs for MEMS microphones
with special focus on ring oscillator based ADCs (RO-ADCs). Firstly, we
study the use of a dual-slope based SAR noise shaped quantizer (SAR-NSQ) in
sigma-delta loops. This quantizer adds and extra level of noise-shaping to the modulator, improving the resolution. The quantizer is explained, and equations
for the noise transfer function (NTF) of a third order sigma-delta using a second
order filter and the NSQ are presented.
Secondly, we move our attention to the topic of RO-ADCs. We present a high
dynamic range MEMS microphone 130nm CMOS chip based on an open-loop
VCO-ADC. This dissertation shows the implementation of the analog front-end
that includes the oscillator and the MEMS interface, with a focus on achieving
low power consumption with low noise and a high dynamic range. The digital
circuitry is left to be explained by the coauthor of the chip in his dissertation. The
chip achieves a 80dBA peak SNDR and 108dB dynamic range with a THD of 1.5%
at 128 dBSPL with a power consumption of 438μW.
After that, we analyze the use of a frequency-dependent-resistor (FDR) to implement
an unsampled feedback loop around the oscillator. The objective is to reduce
distortion. Additionally phase noise mitigation is achieved. A first topology
including an operational amplifier to increase the loop gain is analyzed. The design
is silicon proven in a 130 nm CMOS chip that achieves a 84 dBA peak SNDR
with an analog power consumption of 600μW. A second topology without the
operational amplifier is also analyzed. Two chips are designed with this topology.
The first chip in 130 nm CMOS is a full VCO-ADC including the frequencyto-
digital converter (F2D). This chip achieves a peak SNDR of 76.6 dBA with a
power consumption of 482μW. The second chip includes only the oscillator and
is implemented in 55nm CMOS. The peak SNDR is 78.15 dBA and the analog
power consumption is 153μW.
To finish this thesis, two circuits that use an FDR with a ring oscillator are
presented. The first is a capacity-to-digital converter (CDC). The second is a filter
made with an FDR and an oscillator intended for voice activity detection tasks
(VAD).En los últimos años, el desarrollo de las tecnologías móviles y las aplicaciones de
machine-learning han aumentado la demanda de micrófonos digitales basados
en MEMS. Los dipositivos móviles tienen varios micrófonos que permiten la cancelación
de ruido, el beamforming o conformación de haces y el reconocimiento
de voz. Con el desarrollo de aplicaciones de aprendizaje automático, el interés
por integrar sensores con redes neuronales ha aumentado. Esto ha impulsado el
interés por desarrollar micrófonos digitales en nodos CMOS nanométricos donde
el front-end analógico y el procesamiento digital del micrófono, que puede
incluir redes neuronales, está integrado en el mismo chip.
Tradicionalmente, los convertidores analógicos-digitales (ADC) en micrófonos
digitales han sido implementados utilizando moduladores Sigma-Delta de
orden elevado. La técnica más común para implementar estos moduladores Sigma-
Delta es el uso de circuitos CMOS de capacidades conmutadas. Recientemente,
para reducir el consumo de potencia y hacerlos más adecuados para las tareas que
requieren una operación continua, como el reconocimiento de palabras clave, los
convertidores Sigma-Delta de capacidades conmutadas has sido mejorados con
el uso de integradores implementados con amplificadores operacionales basados
en inversores CMOS. Alternativamente, los Sigma-Delta de capacidades conmutadas
han sido reemplazados por moduladores en tiempo continuo. No obstante,
en ambas implementaciones, la señal de entrada es codificada en voltaje durante
el proceso de conversión, lo que hace que la integración en nodos CMOS más
pequeños sea complicada debido a la menor tensión de alimentación.
Una técnica alternativa consiste en codificar la señal de entrada en tiempo (o
frecuencia) en lugar de tensión. Esto es lo que hacen los convertidores de codificación
temporal. Recientemente, los convertidores de codificación temporal
han ganado popularidad ya que son más adecuados para nodos CMOS nanométricos
que los convertidores Sigma-Delta. Entre los que más interés han despertado
encontramos los ADCs basados en osciladores controlados por tensión
(VCO-ADC). Los VCO-ADC se pueden implementar usando osciladores en anillo
(RO) implementados con inversores CMOS y circuitos digitales. Esta familia
de convertidores también tiene conformado de ruido. Esto los convierte en una
alternativa muy interesante para la implementación de convertidores en nodos
CMOS nanométricos. Sin embargo, dos problemas principales están presentes en
este tipo de ADCs debidos ambos a las no idealidades del oscilador. El primero
de los problemas es la presencia de ruido de fase en el oscilador, lo que reduce la resolución del ADC. El segundo es la curva de conversion voltaje-frecuencia no
lineal del oscilador, lo que causa distorsión a amplitudes medias y altas.
En esta tesis analizamos el uso de ADCs de codificación temporal para micrófonos
MEMS, con especial interés en ADCS basados en osciladores de anillo
(RO-ADC). En primer lugar, estudiamos el uso de un cuantificador SAR con conformado
de ruido (SAR-NSQ) en moduladores Sigma-Delta. Este cuantificador
agrega un orden adicional de conformado de ruido al modulador, mejorando la
resolución. En este documento se explica el cuantificador y obtienen las ecuaciones
para la función de transferencia de ruido (NTF) de un sigma-delta de tercer
orden usando un filtro de segundo orden y el NSQ.
En segundo lugar, dirigimos nuestra atención al tema de los RO-ADC. Presentamos
el chip de un micrófono MEMS de alto rango dinámico en CMOS de
130 nm basado en un VCO-ADC de bucle abierto. En esta tesis se explica la implementación
del front-end analógico que incluye el oscilador y la interfaz con
el MEMS. Esta implementación se ha llevado a cabo con el objetivo de lograr un
bajo consumo de potencia, un bajo nivel de ruido y un alto rango dinámico. La
descripción del back-end digital se deja para la tesis del couator del chip. La
SNDR de pico del chip es de 80dBA y el rango dinámico de 108dB con una THD
de 1,5% a 128 dBSPL y un consumo de potencia de 438μW.
Finalmente, se analiza el uso de una resistencia dependiente de frecuencia
(FDR) para implementar un bucle de realimentación no muestreado alrededor
del oscilador. El objetivo es reducir la distorsión. Además, también se logra la
mitigación del ruido de fase del oscilador. Se analyza una primera topologia de
realimentación incluyendo un amplificador operacional para incrementar la ganancia
de bucle. Este diseño se prueba en silicio en un chip CMOS de 130nm que
logra un pico de SNDR de 84 dBA con un consumo de potencia de 600μW en la
parte analógica. Seguidamente, se analiza una segunda topología sin el amplificador
operacional. Se fabrican y miden dos chips diseñados con esta topologia.
El primero de ellos en CMOS de 130 nm es un VCO-ADC completo que incluye
el convertidor de frecuencia a digital (F2D). Este chip alcanza un pico SNDR de
76,6 dBA con un consumo de potencia de 482μW. El segundo incluye solo el oscilador
y está implementado en CMOS de 55nm. El pico SNDR es 78.15 dBA y el
el consumo de potencia analógica es de 153μW.
Para cerrar esta tesis, se presentan dos circuitos que usan la FDR con un oscilador
en anillo. El primero es un convertidor de capacidad a digital (CDC). El
segundo es un filtro realizado con una FDR y un oscilador, enfocado a tareas de
detección de voz (VAD).Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidente: Antonio Jesús Torralba Silgado.- Secretaria: María Luisa López Vallejo.- Vocal: Pieter Rombout
Análisis y diseño de filtros paso banda basados en VCO para aplicaciones de extracción de características vocales
El objetivo del presente trabajo es el estudio, diseño e implementación de una novedosa arquitectura de filtros paso banda basados en VCO, con aplicación directa en tareas de extracción de características vocales.
Partiendo del modelo a nivel de sistema del filtro analógico clásico (filtro de variables de estado), se plantean las ventajas de un modelo basado en VCO, conduciéndolo así hasta el modelo final diseñado, mostrando los resultados obtenidos en simulación.
Además, se propone una posible implementación hardware del modelo, realizando así una primera aproximación al diseño a nivel de circuito. Se muestran también simulaciones de las distintas partes que forman el circuito, además de una estimación del consumo de cada una de ellas.
Posteriormente, se realiza un análisis de los resultados obtenidos, tanto a nivel de sistema como a nivel de circuito. Además, se exponen los resultados de simulación de las medidas de energía en un banco de filtros ante distintas señales de entrada. De esta manera, se obtienen patrones de la señal de entrada que posteriormente pueden ser introducidas en redes neuronales o árboles de decisión, con el objetivo de detectar la existencia de eventos.Máster Universitario en Ingeniería de Sistemas Electrónicos y Aplicaciones. Curso 2018/201
Energy autonomous systems : future trends in devices, technology, and systems
The rapid evolution of electronic devices since the beginning of the nanoelectronics era has brought about exceptional computational power in an ever shrinking system footprint. This has enabled among others the wealth of nomadic battery powered wireless systems (smart phones, mp3 players, GPS, …) that society currently enjoys. Emerging integration technologies enabling even smaller volumes and the associated increased functional density may bring about a new revolution in systems targeting wearable healthcare, wellness, lifestyle and industrial monitoring applications
2022 roadmap on neuromorphic computing and engineering
Modern computation based on von Neumann architecture is now a mature cutting-edge science. In the von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer is responsible for a large part of the power consumption. The next generation computer technology is expected to solve problems at the exascale with 10 calculations each second. Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically built-in capabilities to learn or deal with complex data as our brain does. These needs can be addressed by neuromorphic computing systems which are inspired by the biological concepts of the human brain. This new generation of computers has the potential to be used for the storage and processing of large amounts of digital information with much lower power consumption than conventional processors. Among their potential future applications, an important niche is moving the control from data centers to edge devices. The aim of this roadmap is to present a snapshot of the present state of neuromorphic technology and provide an opinion on the challenges and opportunities that the future holds in the major areas of neuromorphic technology, namely materials, devices, neuromorphic circuits, neuromorphic algorithms, applications, and ethics. The roadmap is a collection of perspectives where leading researchers in the neuromorphic community provide their own view about the current state and the future challenges for each research area. We hope that this roadmap will be a useful resource by providing a concise yet comprehensive introduction to readers outside this field, for those who are just entering the field, as well as providing future perspectives for those who are well established in the neuromorphic computing community
Advanced Trends in Wireless Communications
Physical limitations on wireless communication channels impose huge challenges to reliable communication. Bandwidth limitations, propagation loss, noise and interference make the wireless channel a narrow pipe that does not readily accommodate rapid flow of data. Thus, researches aim to design systems that are suitable to operate in such channels, in order to have high performance quality of service. Also, the mobility of the communication systems requires further investigations to reduce the complexity and the power consumption of the receiver. This book aims to provide highlights of the current research in the field of wireless communications. The subjects discussed are very valuable to communication researchers rather than researchers in the wireless related areas. The book chapters cover a wide range of wireless communication topics
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
Ultra-Low-Power Uwb Impulse Radio Design: Architecture, Circuits, And Applications
Recent advances in home healthcare, environmental sensing, and low power computing have created a need for wireless communication at very low power for low data rate applications. Due to higher energy/bit requirements at lower data -rate, achieving power levels low enough to enable long battery lifetime (~10 years) or power-harvesting supplies have not been possible with traditional approaches. Dutycycled radios have often been proposed in literature as a solution for such applications due to their ability to shut off the static power consumption at low data rates. While earlier radio nodes for such systems have been proposed based on a type of sleepwake scheduling, such implementations are still power hungry due to large synchronization uncertainty (~1[MICRO SIGN]s). In this dissertation, we utilize impulsive signaling and a pulse-coupled oscillator (PCO) based synchronization scheme to facilitate a globally synchronized wireless network. We have modeled this network over a widely varying parameter space and found that it is capable of reducing system cost as well as providing scalability in wireless sensor networks. Based on this scheme, we implemented an FCC compliant, 3-5GHz, timemultiplexed, dual-band UWB impulse radio transceiver, measured to consume only 20[MICRO SIGN]W when the nodes are synchronized for peer-peer communication. At the system level the design was measured to consume 86[MICRO SIGN]W of power, while facilitating multi- hop communication. Simple pulse-shaping circuitry ensures spectral efficiency, FCC compliance and ~30dB band-isolation. Similarly, the band-switchable, ~2ns turn-on receiver implements a non-coherent pulse detection scheme that facilitates low power consumption with -87dBm sensitivity at 100Kbps. Once synchronized the nodes exchange information while duty-cycling, and can use any type of high level network protocols utilized in packet based communication. For robust network performance, a localized synchronization detection scheme based on relative timing and statistics of the PCO firing and the timing pulses ("sync") is reported. No active hand-shaking is required for nodes to detect synchronization. A self-reinforcement scheme also helps maintain synchronization even in the presence of miss-detections. Finally we discuss unique ways to exploit properties of pulse coupled oscillator networks to realize novel low power event communication, prioritization, localization and immediate neighborhood validation for low power wireless sensor applications
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