172 research outputs found

    130nm CMOS SAR-ADC with Low Complexity Digital Control Logic

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    This paper reports on an original approach to design the digital control logic of a Successive Approximation Register Analog to Digital Converter, where no sequencers or code registers are used. It turns out a low complexity digital circuitry, which is applied to the design of a 130nm CMOS 8-bit SAR ADC. The simulations demonstrate that the proposed digital control logic correctly works leading to an Analog to Digital Converter exhibiting performances well aligned with the literature in terms of linearity, dissipated power, and energy spent per bit generation

    An 8-Bit Analog-to-Digital Converter for Battery Operated Wireless Sensor Nodes

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    Wireless sensing networks (WSNs) collect analog information transduced into the form of a voltage or current. This data is typically converted into a digital representation of the value and transmitted wirelessly using various modulation techniques. As the available power and size is limited for wireless sensor nodes in many applications, a medium resolution Analog-to-Digital Converter (ADC) is proposed to convert a sensed voltage with moderate speeds to lower power consumption. Specifications also include a rail-to-rail input range and minimized errors associated with offset, gain, differential nonlinearity, and integral nonlinearity. To achieve these specifications, an 8-bit successive approximation register ADC is developed which has a conversion time of nine clock cycles. This ADC features a charge scaling array included to achieve minimized power consumption and area by reducing unit capacitance in the digital-to-analog converter. Furthermore, a latched comparator provides fast decisions utilizing positive feedback. The ADC was designed and simulated using Cadence Virtuoso with parasitic extraction over expected operating temperature range of 0 – 85°C. The design was fabricated using TSMC’s 65 nanometer RF GP process and tested on a printed circuit board to verify design specifications. The measured results for the device show an offset and gain error of +7 LSB and 31.1 LSB, respectively, and a DNL range of -0.9 LSB to +0.8 LSB and an INL range of approximately -4.6 LSB to +12 LSB. The INL is much improved in regard to the application of the temperature sensor. The INL for this region of interest is from -3.5 LSB to +2.8 LSB

    A 0.0022 mm<sup>2</sup> 10 bit 20 MS/s SAR ADC with Passive Single-Ended-to-Differential-Converter

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    This paper proposes a passive switched-capacitor single-ended-to-differential-converter (SDC) as a front-end of a differential SAR ADC, such that it can convert single-ended input signals. As the SDC is passive, the overall solution is power-efficient compared to active SDC solutions, and is especially suitable for lower/medium resolutions. As opposed to active SDC solutions with a static bias current, the proposed switched-capacitor network only consumes dynamic power, such that its consumption scales linearly with the sampling frequency. This paper discusses the basic concept of the proposed scheme, and analyzes the impact of noise and other imperfections, describes the trade-offs for power and area, and discusses the consequences for the input driver. A prototype implementation in 65nm CMOS achieves a figure-of-merit of 6.1fJ/conversion-step at 20MS/s, while reaching an SNDR of 54.7dB up to Nyquist and occupying a chip area of only 60μ m times 36μ m.</p

    Static and dynamic nonlinearity compensation techniques for high performance current-steering digital-to-analog converters

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    High-speed high-accuracy digital-to-analog converters (DACs) are the crucial building blocks for many signal processing and telecommunication systems. The current-steering architecture is extensively used for these applications. With different decoding schemes--binary-weighted, unary-coded, and segment-coded, current-steering DACs are realized by groups of matched current sources. Their performance is limited by many nonlinear mechanisms such as random mismatch errors, gradient effect, code and voltage dependence of finite output impedance, nonlinear settling time, charge injection, and switch timing errors. In this thesis, two nonlinearity compensation techniques are presented to improve the overall performance of the current-steering DACs. The first design technique is a novel digital calibration technique--complete-folding, which effectively compensates the random mismatch errors by selectively regrouping current sources into a fully binary-weighted array based on current comparisons after chip fabrication. The implementation only requires an analog current comparator and some digital circuitry. The minimum requirement of analog circuits makes complete-folding calibration suitable for DAC design in the low-voltage process. Statistical results with a behavioral model of a 14-bit segmented DAC in MATLAB show that complete-folding calibration can reduce the total gate area of current sources by a factor of almost 1200 compared to the DAC without using any calibration. Additional results also show that this new calibration technique has the superior performance in compensating random mismatch errors as compared to state-of-the-art. The second design technique is a novel output impedance linearization technique that very effectively reduces the code and voltage dependence of finite output impedance. The linearization is achieved by using a small DAC switched with control signals opposite to those for the main DAC. The area and power overhead is less than 5% of the main DAC. Simulation results with a 14-bit segmented current-steering DAC in standard 0.18μm CMOS process show that the DAC\u27s integral nonlinearity (INL) due to finite output impedance is improved by almost 5 bits. Additional results show that this technique is very robust to random mismatch errors. Moreover, not only the static linearity is improved, but most importantly there is a large dynamic linearity enhancement by output impedance linearization. Simulation results show that spurious-free dynamic range (SFDR) can be improved by almost 30 dB at the low signal frequencies and more than 8 dB for the high signal frequencies up to Nyquist rate while sampling at 500MS/s

    Digitally Interfaced Analog Correlation Filter System for Object Tracking Applications

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    Advanced correlation filters have been employed in a wide variety of image processing and pattern recognition applications such as automatic target recognition and biometric recognition. Among those, object recognition and tracking have received more attention recently due to their wide range of applications such as autonomous cars, automated surveillance, human-computer interaction, and vehicle navigation.Although digital signal processing has long been used to realize such computational systems, they consume extensive silicon area and power. In fact, computational tasks that require low to moderate signal-to-noise ratios are more efficiently realized in analog than digital. However, analog signal processing has its own caveats. Mainly, noise and offset accumulation which degrades the accuracy, and lack of a scalable and standard input/output interface capable of managing a large number of analog data.Two digitally-interfaced analog correlation filter systems are proposed. While digital interfacing provided a standard and scalable way of communication with pre- and post-processing blocks without undermining the energy efficiency of the system, the multiply-accumulate operations were performed in analog. Moreover, non-volatile floating-gate memories are utilized as storage for coefficients. The proposed systems incorporate techniques to reduce the effects of analog circuit imperfections.The first system implements a 24x57 Gilbert-multiplier-based correlation filter. The I/O interface is implemented with low-power D/A and A/D converters and a correlated double sampling technique is implemented to reduce offset and lowfrequency noise at the output of analog array. The prototype chip occupies an area of 3.23mm2 and demonstrates a 25.2pJ/MAC energy-efficiency at 11.3 kVec/s and 3.2% RMSE.The second system realizes a 24x41 PWM-based correlation filter. Benefiting from a time-domain approach to multiplication, this system eliminates the need for explicit D/A and A/D converters. Careful utilization of clock and available hardware resources in the digital I/O interface, along with application of power management techniques has significantly reduced the circuit complexity and energy consumption of the system. Additionally, programmable transconductance amplifiers are incorporated at the output of the analog array for offset and gain error calibration. The prototype system occupies an area of 0.98mm2 and is expected to achieve an outstanding energy-efficiency of 3.6pJ/MAC at 319kVec/s with 0.28% RMSE

    Linearization of Time-encoded ADCs Architectures for Smart MEMS Sensors in Low Power CMOS Technology

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    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

    Bidirectional Neural Interface Circuits with On-Chip Stimulation Artifact Reduction Schemes

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    Bidirectional neural interfaces are tools designed to “communicate” with the brain via recording and modulation of neuronal activity. The bidirectional interface systems have been adopted for many applications. Neuroscientists employ them to map neuronal circuits through precise stimulation and recording. Medical doctors deploy them as adaptable medical devices which control therapeutic stimulation parameters based on monitoring real-time neural activity. Brain-machine-interface (BMI) researchers use neural interfaces to bypass the nervous system and directly control neuroprosthetics or brain-computer-interface (BCI) spellers. In bidirectional interfaces, the implantable transducers as well as the corresponding electronic circuits and systems face several challenges. A high channel count, low power consumption, and reduced system size are desirable for potential chronic deployment and wider applicability. Moreover, a neural interface designed for robust closed-loop operation requires the mitigation of stimulation artifacts which corrupt the recorded signals. This dissertation introduces several techniques targeting low power consumption, small size, and reduction of stimulation artifacts. These techniques are implemented for extracellular electrophysiological recording and two stimulation modalities: direct current stimulation for closed-loop control of seizure detection/quench and optical stimulation for optogenetic studies. While the two modalities differ in their mechanisms, hardware implementation, and applications, they share many crucial system-level challenges. The first method aims at solving the critical issue of stimulation artifacts saturating the preamplifier in the recording front-end. To prevent saturation, a novel mixed-signal stimulation artifact cancellation circuit is devised to subtract the artifact before amplification and maintain the standard input range of a power-hungry preamplifier. Additional novel techniques have been also implemented to lower the noise and power consumption. A common average referencing (CAR) front-end circuit eliminates the cross-channel common mode noise by averaging and subtracting it in analog domain. A range-adapting SAR ADC saves additional power by eliminating unnecessary conversion cycles when the input signal is small. Measurements of an integrated circuit (IC) prototype demonstrate the attenuation of stimulation artifacts by up to 42 dB and cross-channel noise suppression by up to 39.8 dB. The power consumption per channel is maintained at 330 nW, while the area per channel is only 0.17 mm2. The second system implements a compact headstage for closed-loop optogenetic stimulation and electrophysiological recording. This design targets a miniaturized form factor, high channel count, and high-precision stimulation control suitable for rodent in-vivo optogenetic studies. Monolithically integrated optoelectrodes (which include 12 µLEDs for optical stimulation and 12 electrical recording sites) are combined with an off-the-shelf recording IC and a custom-designed high-precision LED driver. 32 recording and 12 stimulation channels can be individually accessed and controlled on a small headstage with dimensions of 2.16 x 2.38 x 0.35 cm and mass of 1.9 g. A third system prototype improves the optogenetic headstage prototype by furthering system integration and improving power efficiency facilitating wireless operation. The custom application-specific integrated circuit (ASIC) combines recording and stimulation channels with a power management unit, allowing the system to be powered by an ultra-light Li-ion battery. Additionally, the µLED drivers include a high-resolution arbitrary waveform generation mode for shaping of µLED current pulses to preemptively reduce artifacts. A prototype IC occupies 7.66 mm2, consumes 3.04 mW under typical operating conditions, and the optical pulse shaping scheme can attenuate stimulation artifacts by up to 3x with a Gaussian-rise pulse rise time under 1 ms.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147674/1/mendrela_1.pd

    Power and area efficient reconfigurable delta sigma ADCs

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    Design of Analog-to-Digital Converters with Embedded Mixing for Ultra-Low-Power Radio Receivers

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    In the field of radio receivers, down-conversion methods usually rely on one (or more) explicit mixing stage(s) before the analog-to-digital converter (ADC). These stages not only contribute to the overall power consumption but also have an impact on area and can compromise the receiver’s performance in terms of noise and linearity. On the other hand, most ADCs require some sort of reference signal in order to properly digitize an analog input signal. The implementation of this reference signal usually relies on bandgap circuits and reference buffers to generate a constant, stable, dc signal. Disregarding this conventional approach, the work developed in this thesis aims to explore the viability behind the usage of a variable reference signal. Moreover, it demonstrates that not only can an input signal be properly digitized, but also shifted up and down in frequency, effectively embedding the mixing operation in an ADC. As a result, ADCs in receiver chains can perform double-duty as both a quantizer and a mixing stage. The lesser known charge-sharing (CS) topology, within the successive approximation register (SAR) ADCs, is used for a practical implementation, due to its feature of “pre-charging” the reference signal prior to the conversion. Simulation results from an 8-bit CS-SAR ADC designed in a 0.13 μm CMOS technology validate the proposed technique
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