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 Alternatively, switched-capacitor based Sigma- Delta modulators have been replaced by continuous time Sigma-Delta converters.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

Time-encoding analog-to-digital converters : bridging the analog gap to advanced digital CMOS? Part 2: architectures and circuits

The scaling of CMOS technology deep into the nanometer range has created challenges for the design of highperformance analog ICs: they remain large in area and power consumption in spite of process scaling. Analog circuits based on time encoding [1], [2], where the signal information is encoded in the waveform transitions instead of its amplitude, have been developed to overcome these issues. While part one of this overview article [3] presented the basic principles of time encoding, this follow-up article describes and compares the main time-encoding architectures for analog-to-digital converters (ADCs) and discusses the corresponding design challenges of the circuit blocks. The focus is on structures that avoid, as much as possible, the use of traditional analog blocks like operational amplifiers (opamps) or comparators but instead use digital circuitry, ring oscillators, flip-flops, counters, an so on. Our overview of the state of the art will show that these circuits can achieve excellent performance. The obvious benefit of this highly digital approach to realizing analog functionality is that the resulting circuits are small in area and more compatible with CMOS process scaling. The approach also allows for the easy integration of these analog functions in systems on chip operating at "digital" supply voltages as low as 1V and lower. A large part of the design process can also be embedded in a standard digital synthesis flow

Low-pass CMOS Sigma-Delta Converter

A crescente necessidade em dar-se uma melhor saúde à população obriga ao desenvolvimento de novos e melhores dispositivos médicos. Atualmente, uma área de desenvolvimento importante é a de dispositivos portáteis para análise de sinais biológicos, tais como o eletrocardiograma ou o electroencefalograma, ajudando os profissionais de saúde a fazer rápidos diagnósticos no terreno, ou mesmo para serem usados por cidadãos que necessitem de vigilância constante. O desenvolvimento destes aparelhos traz novos desafios para a comunidade cientifica, nomeadamente na interface analógico/digital, na qualidade dos dados obtidos e no gasto energético. Para se conceber um bom dispositivos médico é necessário um conversor analógico/digital para frequências baixas, com baixo consumo energético e elevada resolução. Esta dissertação começa por fornecer ao leitor a teoria básica sobre conversores analógico/digital (ADC) e estado de arte. Como principal objetivo do trabalho desenvolvido, é descrito o desenho de um ADC baseado numa arquitetura Sigma-Delta que vá de encontro aos requisitos mencionados. O conversor foi implementado numa tecnologia 130 nm CMOS, usando uma frequência de amostragem de 1 MHz, com uma largura de banda de 1 kHz e tensão de alimentação 1,2 V. É usada, nos integradores do sigma-delta, uma invulgar tipologia de Opamp de forma a obter um ganho elevado, sem recurso a técnicas cascode. O quantizador possui uma resolução de 1,5 bits e é realizado com dois comparadores dinâmicos, de forma a minimizar o consumo energético.The growing need to provide better health for the population requires the development of new and better medical devices. Portable devices for the analysis of biological signals, such as the electrocardiogram or electroencephalogram, is nowadays an important development, helping health professionals to come up with fast diagnoses on the field, or even for use by citizens who require constant vigilance . Developing these devices brings new challenges to the scientific community, namely at the analog/digital interface, the quality of data and power consumption. In order to design a good medical device it is necessary an analog/digital converter for low frequencies, with low power consumption and high resolution. This dissertation begins by providing the reader with the basic theory of analog/digital (ADC) and its state of the art. The main goal of the work is the design of an ADC based on a Sigma-Delta architecture that meets the necessary medical requirements. The converter was implemented in a 130 nm CMOS technology using a sampling frequency of 1 MHz, with a bandwidth of 1 kHz, and a source voltage of 1.2 V. The integrators of sigma-delta employs an unusual Opamp typology in order to reach a high gain, without resourcing to cascode techniques. The quantizer has a resolution of 1.5 bits and is realized with two dynamic comparators, in order to minimize power consumption

First order sigma-delta modulator of an oversampling ADC design in CMOS using floating gate MOSFETS

We report a new architecture for a sigma-delta oversampling analog-to-digital converter (ADC) in which the first order modulator is realized using the floating gate MOSFETs at the input stage of an integrator and the comparator. The first order modulator is designed using an 8 MHz sampling clock frequency and implemented in a standard 1.5µm n-well CMOS process. The decimator is an off-chip sinc-filter and is programmed using the VERILOG and tested with Altera Flex EPF10K70RC240 FPGA board. The ADC gives an 8-bit resolution with a 65 kHz bandwidth

Signal acquisition challenges in mobile systems

In recent decades, the advent of mobile computing has changed human lives by providing information that was not available in the past. The mobile computing platform opens a new door to the connected world in which various forms of hand-held and wearable systems are ubiquitous. A single mobile device plays multiple roles and shapes human lives towards a better future. In these systems, sensor-based data acquisition plays an essential role in generating and providing useful information. The increased number of sensors is embedded in a single device in order to process various signal modalities. In practice, more than 30 data converters are required in designing a mobile system in which the data-converting blocks become among the most power-hungry components in battery-operated systems. Due to the increased variety of sensors, mobile systems are meant to face several obstacles. For example, the increased number of sensors increase system power consumption during the system operation. The increased power consumption directly affects operation time because mobile systems are powered by a limited energy source. Moreover, an increased amount of information also gives rise to bandwidth problems in communication due to the increased volume of data transmission. Also, this system design requires a larger area in a silicon die so that multiple signal paths can be placed without cross-channel interference. Therefore, the system design has presented a challenge in terms of trying to resolve the design constraints such as power consumption, bandwidth usage, storage space, and design complexity issues. To overcome these obstacles, in this dissertation, efficient data acquisition and processing methods are investigated. Specifically, this thesis considers the problems of energy-efficient sampling and binary event detection. This dissertation begins by presenting a new signal sampling scheme that enables higher precision signal conversion in compressed-sensing-based signal acquisition. The proposed scheme is based on the popular successive approximation register and employs a modified compressive sensing technique to increase the resolution of successive-approximation-register (SAR) analog-to-digital converter (ADC) architecture. Circuit-level architecture is discussed to implement the proposed scheme using the SAR ADC architecture. A non-uniform quantization scheme is proposed and it improves data quality after data acquisition. The proposed scheme is expected to be used for medium- or high- frequency data conversion. Secondly, the possibility of using fewer ADCs than channels is studied by leveraging sparse-signal representation and blind-source-separation (BSS) techniques. In particular, this dissertation examines the problem of using a single ADC or quantizer system for digitizing multi-channel inputs. Mixing and de-mixing strategies are extensively studied for sampling frequency-sparse signals and the proposed multi-channel architecture can be easily implemented using today's analog/mixed-signal circuits. The third part of this dissertation investigates a binary hypothesis testing problem. In mobile devices such as smartphones and tablet PCs, a major portion of energy is consumed in user interfaces (LCD display and touch input processing). For accurate detection and better user interface, energy-efficient sensing and detection schemes are necessary to manage multiple sensor inputs. A highly efficient detection scheme is presented that can detect binary events reliably with a fraction of the energy consumption required in the conventional energy detection.Electrical and Computer Engineerin

A Robust 96.6-dB-SNDR 50-kHz-Bandwidth Switched-Capacitor Delta-Sigma Modulator for IR Imagers in Space Instrumentation

Infrared imaging technology, used both to study deep-space bodies' radiation and environmental changes on Earth, experienced constant improvements in the last few years, pushing data converter designers to face new challenges in terms of speed, power consumption and robustness against extremely harsh operating conditions. This paper presents a 96.6-dB-SNDR (Signal-to-Noise-plus-Distortion Ratio) 50-kHz-bandwidth fourth-order single-bit switched-capacitor delta-sigma modulator for ADC operating at 1.8 V and consuming 7.9 mW fit for space instrumentation. The circuit features novel Class-AB single-stage switched variable-mirror amplifiers (SVMAs) enabling low-power operation, as well as low sensitivity to both process and temperature deviations for the whole modulator. The physical implementation resulted in a 1.8-mm 2 chip integrated in a standard 0.18-μm 1-poly-6-metal (1P6M) CMOS technology, and it reaches a 164.6-dB Schreier figure of merit from experimental SNDR measurements without making use of any clock bootstrapping, analog calibration, nor digital compensation technique. When coupled to a IR imager, the current design allows more than 50 frames per minute with a resolution of 16 effective number of bits (ENOB) while consuming less than 300 mW

A Low Power Sigma-Delta Modulator with Hybrid Architecture

Analogue-to-digital converters (ADC) using oversampling technology and Σ-∆ modulation mechanism are widely applied in digital audio systems. This paper presents an audio modulator with high accuracy and low power consumption by using discrete second-order feedforward structure. A 5-bit SAR (Successive-approximation-register) quantizer is integrated into the chip, which reduces the number of comparators and the power consumption of the quantizer compared with Flash ADC type quantizers. An analogue passive adder is used to sum the input signals and it is embedded in a SAR ADC composed of capacitor array and a dynamic comparator which has no static power consumption. To validate the design concept, the designed modulator is developed in a 180 nm CMOS process. The peak SNDR (signal to noise distortion ratio) is calculated as 106 dB and the total power consumption of the chip is recorded as 3.654 mW at the chip supply voltage of 1.8 V. The input sine wave of 0 to 25 kHz is sampled at a sampling frequency of 3.2 Ms/s. Moreover, the results achieve 16-bit ENOB (effective number of bits) when the amplitude of the input signal is varied between 0.15 V to 1.65 V. By comparing with other modulators which were realized by 180nm CMOS process, the proposed architecture outperforms with lower power consumption

Ring-oscillator with multiple transconductors for linear analog-to-digital conversion

This paper proposes a new circuit-based approach to mitigate nonlinearity in open-loop ring-oscillator-based analog-to-digital converters (ADCs). The approach consists of driving a current-controlled oscillator (CCO) with several transconductors connected in parallel with different bias conditions. The current injected into the oscillator can then be properly sized to linearize the oscillator, performing the inverse current-to-frequency function. To evaluate the approach, a circuit example has been designed in a 65-nm CMOS process, leading to a more than 3-ENOB enhancement in simulation for a high-swing differential input voltage signal of 800-mVpp, with considerable less complex design and lower power and expected area in comparison to state-of-the-art circuit based solutions. The architecture has also been checked against PVT and mismatch variations, proving to be highly robust, requiring only very simple calibration techniques. The solution is especially suitable for high-bandwidth (tens of MHz) medium-resolution applications (10–12 ENOBs), such as 5G or Internet-of-Things (IoT) devices.This research was funded by Project TEC2017-82653-R, Spain