A 77.3-dB SNDR 62.5-kHz Bandwidth Continuous-Time Noise-Shaping SAR ADC With Duty-Cycled G_m-C Integrator

This article presents a first-order continuous-time (CT) noise-shaping successive-approximation-register (NS-SAR) analog-to-digital converter (ADC). Different from other NS-SAR ADCs in literature, which are discrete-time (DT), this ADC utilizes a CT Gm-C integrator to realize an inherent anti-aliasing function. To cope with the timing conflict between the DT SAR ADC and the CT integrator, the sampling switch of the SAR ADC is removed, and the integrator is duty cycled to leave 5% of the sampling clock period for the SAR conversion. Redundancy is added to track the varying ADC input due to the absence of the sampling switch. A theoretical analysis shows that the 5% duty-cycling has negligible effects on the signal transfer function (STF) and the noise transfer function. The output swing and linearity requirements for the integrator are also relaxed thanks to the inherent feedforward path in the NS-SAR ADC architecture. Fabricated in 65-nm CMOS, the prototype achieves 77.3-dB peak signal-to-noise and distortion ratio (SNDR) in a 62.5-kHz bandwidth while consuming 13.5μ W, leading to a Schreier figure of merit (FoM) of 174.0 dB. Moreover, it provides 15-dB attenuation in the alias band.</p

Design and automation techniques for hIgh-performance mixed-signal circuits

In the era of ubiquitous sensing environment, the modern electronic system expands our perception of the outside world. Analog/mixed-signal circuit has played a critical role to bridge the physical and digital worlds. The boom of Internet-of-Things (IoT), bio-sensing, and digital camera calls for versatile high-performance mixed-signal circuits and the corresponding automated design methodology. However, high-performance analog circuits are area or power hungry. Moreover, the design cost is prohibitively expensive. To address these challenges, this dissertation explores solutions from both the design and automation techniques. Analog-to-digital converter (ADC) is an important subset of analog/mixed-signal circuits. Continuous time Delta-Sigma modulator (CTDSM) is a popular design choice for high-speed and high-resolution designs. CTDSMs feature a higher power efficiency than their discrete-time (DT) counterpart. The first work presents a high-speed 4th-order DSM featuring the CT-DT hybridization and an efficient excess-loop-delay (ELD) compensation technique in the charge domain. Compared to prior high-order CTDSMs, the proposed hybrid DSM achieves 4th-order noise shaping with single operational trans-conductance amplifier (OTA). Minimized number of OTAs reduces power and enhances stability. On top of that, an efficient ELD compensation technique is implemented by utilizing the inherent capacitor digital-to-analog converter (CDAC) of SAR. Fabricated in 40 nm CMOS, the prototype ADC achieved a peak Schreier Figure-of-Merits (FoM) of 176.1 dB, marking 4 dB improvement over prior arts. The second project explores the techniques to reduce the area consumption of high-resolution CTDSMs. The performance of existing high-resolution CTDSMs is limited by the feedback DAC. The stringent non-linearity requirement leads to the large area of DAC. To address this limitation, a low-complexity hardware-based 2nd-order dynamic-element-matching (DEM) is proposed. The partial sorter applied to the DEM minimizes the hardware cost. Moreover, feedforward path assisted loop filter adapts the highly-linear integrator design to the low power supply voltage. With these techniques combined, the prototype shows a feasible design pattern to achieve compact-area, high-resolution design at advanced technology nodes. A prototype fabricated in 40 nm CMOS measured 95dB SNDR, occupying only 0.37 mm² area. After the exploration of pushing the ADC performance boundary, this dissertation also demonstrates the automated design methodology. The design cost of high-performance mixed-signal circuit grows exponentially with the technology scaling. Existing analog automation techniques cannot handle practical circuit design constraints (e.g. robustness against variations). The third work presents RobustAnalog, a variation-aware analog circuit optimization via multi-task reinforcement learning (RL) and task-space pruning. RobustAnalog is mainly designed to tackle the process-voltage-temperature (PVT) robustness in the analog design. Correlations between similar variations are modeled and conflicts between distinct variations are mitigated. With task pruning, a small-sized proxy training task set is formed. The pruning reduces the queries to the full task set. Compared with the popular blackbox optimization methods, RobustAnalog significantly reduces the simulation cost. Therefore, RobustAnalog shows the staggering progress towards analog automation techniques that can be applied to real silicon conditions.Electrical and Computer Engineerin

A 65nm continuous-time sigma-delta modulator with limited OTA DC gain compensation

This paper explores the effects of compensating the performance degradation in high-speed Continuous-Time Sigma-Delta modulators when the loop integrators are implemented through limited gain Operational Transconductance Amplifiers. Yet, the low DC-gain strongly affects both integrator magnitude and phase responses, with a reduction in the overall effective number of bits. This work models the degradation as due to a signal-dependent memory-less perturbation and theoretically studies its compensation by feeding an opposite signal back to the integrator input. The implementation and experimental results on a 65nm CMOS 2nd order prototype evaluate the performance increase with this technique, where no other compensation, nor any digital calibration, is included. Tested in different conditions, the compensated prototype improves more than 1.5 bit the ENoB with respect to the uncompensated counterpart. For a sampling frequency of 500 MHz the power consumption is 1.7mW, resulting in a 477.2fJ/conv-lev Walden and a 148.8dB Schreirer Figures of Merit

Modulador Σ∆ en tiempo continuo con cuantificador de baja resolución

El diseño de sistemas electrónicos presenta una tendencia en la autonomía energética y la reducción de la masa y dimensiones de los dispositivos. Los circuitos electronicos para el procesamiento en la conversión de datos del dominio analógico al digital siguen presentando retos importantes. En el diseño de covertidores, la modulación Sigma-Delta sigue contribuyendo a la reducción de recursos y la resilencia a los factores ambientales y la deriva temporal. Los moduladores Sigma-Delta de tiempo continuo se han convertido en una buena opcion para aplicaciones que requieren un bajo consumo de potencia y una alta velocidad en el procesamiento de la información. Este trabajo se basa en el estudio de moduladores Sigma-Delta de tiempo continuo con cuantificador de un bit mostrando el análisis y modelado. La propuesta resulta la topología un modulador Sigma-Delta TC de tercer orden primeramente modelado en bloques de Simulink y posteriormente descrito con algunos bloques usando lenguaje de Verilog-A, alcanzando un SNR de 81.7 dB y una resolución de 13 bits usando una relación de sobre muestreo de 46. Como elemento innovador, la arquitectura propuesta se ha usado como opción para sustituir en transmisores RF los bloques del mezclador y el convertidor analógico digital (ADC).

Analog Front-End Circuits for Massive Parallel 3-D Neural Microsystems.

Understanding dynamics of the brain has tremendously improved due to the progress in neural recording techniques over the past five decades. The number of simultaneously recorded channels has actually doubled every 7 years, which implies that a recording system with a few thousand channels should be available in the next two decades. Nonetheless, a leap in the number of simultaneous channels has remained an unmet need due to many limitations, especially in the front-end recording integrated circuits (IC). This research has focused on increasing the number of simultaneously recorded channels and providing modular design approaches to improve the integration and expansion of 3-D recording microsystems. Three analog front-ends (AFE) have been developed using extremely low-power and small-area circuit techniques on both the circuit and system levels. The three prototypes have investigated some critical circuit challenges in power, area, interface, and modularity. The first AFE (16-channels) has optimized energy efficiency using techniques such as moderate inversion, minimized asynchronous interface for data acquisition, power-scalable sampling operation, and a wide configuration range of gain and bandwidth. Circuits in this part were designed in a 0.25μm CMOS process using a 0.9-V single supply and feature a power consumption of 4μW/channel and an energy-area efficiency of 7.51x10^15 in units of J^-1Vrms^-1mm^-2. The second AFE (128-channels) provides the next level of scaling using dc-coupled analog compression techniques to reject the electrode offset and reduce the implementation area further. Signal processing techniques were also explored to transfer some computational power outside the brain. Circuits in this part were designed in a 180nm CMOS process using a 0.5-V single supply and feature a power consumption of 2.5μW/channel, and energy-area efficiency of 30.2x10^15 J^-1Vrms^-1mm^-2. The last AFE (128-channels) shows another leap in neural recording using monolithic integration of recording circuits on the shanks of neural probes. Monolithic integration may be the most effective approach to allow simultaneous recording of more than 1,024 channels. The probe and circuits in this part were designed in a 150 nm SOI CMOS process using a 0.5-V single supply and feature a power consumption of only 1.4μW/channel and energy-area efficiency of 36.4x10^15 J^-1Vrms^-1mm^-2.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/98070/1/ashmouny_1.pd