Noise shaping Asynchronous SAR ADC based time to digital converter

Time-to-digital converters (TDCs) are key elements for the digitization of timing information in modern mixed-signal circuits such as digital PLLs, DLLs, ADCs, and on-chip jitter-monitoring circuits. Especially, high-resolution TDCs are increasingly employed in on-chip timing tests, such as jitter and clock skew measurements, as advanced fabrication technologies allow fine on-chip time resolutions. Its main purpose is to quantize the time interval of a pulse signal or the time interval between the rising edges of two clock signals. Similarly to ADCs, the performance of TDCs are also primarily characterized by Resolution, Sampling Rate, FOM, SNDR, Dynamic Range and DNL/INL. This work proposes and demonstrates 2nd order noise shaping Asynchronous SAR ADC based TDC architecture with highest resolution of 0.25 ps among current state of art designs with respect to post-layout simulation results. This circuit is a combination of low power/High Resolution 2nd Order Noise Shaped Asynchronous SAR ADC backend with simple Time to Amplitude converter (TAC) front-end and is implemented in 40nm CMOS technology. Additionally, special emphasis is given on the discussion on various current state of art TDC architectures.Electrical and Computer Engineerin

A time-based energy-efficient analog-to-digital converter

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2006.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (leaves 123-129).Dual-slope converters use time to perform analog-to-digital conversion but require 2N+1 clock cycles to achieve N bits of precision. We describe a novel algorithm that also uses time to perform analog-to-digital conversion but requires 5N clock cycles to achieve N bits of precision via a successive sub-ranging technique. The algorithm requires one asynchronous comparator, two capacitors, one current source, and a state machine. Amplification of two is achieved without the use of an explicit amplifier by simply doing things twice in time. The use of alternating Voltage-to-Time and Time-to-Voltage conversions provides natural error cancellation of comparator offset and delay, 1/f noise, and switching charge-injection. The use of few components and an effcient mechanism for amplification and error cancellation allow for energy-effcient operation: In a 0.35 [mu]m implementation, we were able to achieve 12 bits of DNL limited precision or 11 bits of thermal noise-limited precision at a sampling frequency of 31.25kHz with 75 [mu] W of total analog and digital power consumption. These numbers yield a thermal noise-limited energy-efficiency of 1.17pJ per quantization level making it one of the most energy-effcient converters to date in the 10 to 12 bit precision range.(cont.) This converter could be useful in low-power hearing aids after analog gain control has been performed on a microphone front-end. An 8 bit audio version of our converter in a 0.18 [mu] m process consumes 960nW and yields an energy-efficiency of 0.12pJ per quantization level, perhaps the lowest ever reported. This converter may be useful in biomedical and sensor-network applications where energy-efficiency is paramount. Our algorithm has inherent advantages in time-to-digital conversion. It can be generalized to easily digitize power-law functions of its input, and it can be used in an interleaved architecture if higher speed is desired.by Heemin Yi Yang.Ph.D

Design and Comparison of Asynchronous FFT Implementations

Fast Fourier Transform (FFT) is a widely used digital signal processing technology in a large variety of applications. For battery-powered embedded systems incorporating FFT, its physical implementation is constrained by strict power consumption, especially during idle periods. Compared to the prevailing clocked synchronous counterpart, quasi-delay insensitive asynchronous circuits offer a series of advantages including flexible timing requirement and lower leakage power, making them ideal choices for these systems. In this thesis work, various FFT configurations were implemented in the low-power Multi-Threshold NULL Convention Logic (MTNCL) paradigm. Analysis illustrates the area and power consumption trends along the changing of the number of points, data widths, and the number of pipeline stages

Design and Comparison of Asynchronous FFT Implementations

Fast Fourier Transform (FFT) is a widely used digital signal processing technology in a large variety of applications. For battery-powered embedded systems incorporating FFT, its physical implementation is constrained by strict power consumption, especially during idle periods. Compared to the prevailing clocked synchronous counterpart, quasi-delay insensitive asynchronous circuits offer a series of advantages including flexible timing requirement and lower leakage power, making them ideal choices for these systems. In this thesis work, various FFT configurations were implemented in the low-power Multi-Threshold NULL Convention Logic (MTNCL) paradigm. Analysis illustrates the area and power consumption trends along the changing of the number of points, data widths, and the number of pipeline stages

Low power VCO-based analog-to-digital conversion

textThis dissertation presents novel two stage ADC architecture with a VCO based second stage. With the scaling of the supply voltages in modern CMOS process it is difficult to design high gain operational amplifiers needed for traditional voltage domain two-stage analog to digital converters. However time resolution continues to improve with the advancement in CMOS technology making VCO-based ADC more attractive. The nonlinearity in voltage-to-frequency transfer function is the biggest challenge in design of VCO based ADC. The hybrid approach used in this work uses a voltage domain first stage to determine the most significant bits and uses a VCO based second stage to quantize the small residue obtained from first stage. The architecture relaxes the gain requirement on the the first stage opamp and also relaxes the linearity requirements on the second stage VCO. The prototype ADC built in 65nm CMOS process achieves 63.7dB SNDR in 10MHz bandwidth while only consuming 1.1mW of power. The performance of the prototype chip is comparable to the state-of-art in terms of figure-of-merit but this new architecture uses significantly less circuit area.Electrical and Computer Engineerin

A Low-Power, Reconfigurable, Pipelined ADC with Automatic Adaptation for Implantable Bioimpedance Applications

Biomedical monitoring systems that observe various physiological parameters or electrochemical reactions typically cannot expect signals with fixed amplitude or frequency as signal properties can vary greatly even among similar biosignals. Furthermore, advancements in biomedical research have resulted in more elaborate biosignal monitoring schemes which allow the continuous acquisition of important patient information. Conventional ADCs with a fixed resolution and sampling rate are not able to adapt to signals with a wide range of variation. As a result, reconfigurable analog-to-digital converters (ADC) have become increasingly more attractive for implantable biosensor systems. These converters are able to change their operable resolution, sampling rate, or both in order convert changing signals with increased power efficiency. Traditionally, biomedical sensing applications were limited to low frequencies. Therefore, much of the research on ADCs for biomedical applications focused on minimizing power consumption with smaller bias currents resulting in low sampling rates. However, recently bioimpedance monitoring has become more popular because of its healthcare possibilities. Bioimpedance monitoring involves injecting an AC current into a biosample and measuring the corresponding voltage drop. The frequency of the injected current greatly affects the amplitude and phase of the voltage drop as biological tissue is comprised of resistive and capacitive elements. For this reason, a full spectrum of measurements from 100 Hz to 10-100 MHz is required to gain a full understanding of the impedance. For this type of implantable biomedical application, the typical low power, low sampling rate analog-to-digital converter is insufficient. A different optimization of power and performance must be achieved. Since SAR ADC power consumption scales heavily with sampling rate, the converters that sample fast enough to be attractive for bioimpedance monitoring do not have a figure-of-merit that is comparable to the slower converters. Therefore, an auto-adapting, reconfigurable pipelined analog-to-digital converter is proposed. The converter can operate with either 8 or 10 bits of resolution and with a sampling rate of 0.1 or 20 MS/s. Additionally, the resolution and sampling rate are automatically determined by the converter itself based on the input signal. This way, power efficiency is increased for input signals of varying frequency and amplitude

New Views for Stochastic Computing: From Time-Encoding to Deterministic Processing

University of Minnesota Ph.D. dissertation.July 2018. Major: Electrical/Computer Engineering. Advisor: David Lilja. 1 computer file (PDF); xi, 149 pages.Stochastic computing (SC), a paradigm first introduced in the 1960s, has received considerable attention in recent years as a potential paradigm for emerging technologies and ''post-CMOS'' computing. Logical computation is performed on random bitstreams where the signal value is encoded by the probability of obtaining a one versus a zero. This unconventional representation of data offers some intriguing advantages over conventional weighted binary. Implementing complex functions with simple hardware (e.g., multiplication using a single AND gate), tolerating soft errors (i.e., bit flips), and progressive precision are the primary advantages of SC. The obvious disadvantage, however, is latency. A stochastic representation is exponentially longer than conventional binary radix. Long latencies translate into high energy consumption, often higher than that of their binary counterpart. Generating bit streams is also costly. Factoring in the cost of the bit-stream generators, the overall hardware cost of an SC implementation is often comparable to a conventional binary implementation. This dissertation begins by proposing a highly unorthodox idea: performing computation with digital constructs on time-encoded analog signals. We introduce a new, energy-efficient, high-performance, and much less costly approach for SC using time-encoded pulse signals. We explore the design and implementation of arithmetic operations on time-encoded data and discuss the advantages, challenges, and potential applications. Experimental results on image processing applications show up to 99% performance speedup, 98% saving in energy dissipation, and 40% area reduction compared to prior stochastic implementations. We further introduce a low-cost approach for synthesizing sorting network circuits based on deterministic unary bit-streams. Synthesis results show more than 90% area and power savings compared to the costs of the conventional binary implementation. Time-based encoding of data is then exploited for fast and energy-efficient processing of data with the developed sorting circuits. Poor progressive precision is the main challenge with the recently developed deterministic methods of SC. We propose a high-quality down-sampling method which significantly improves the processing time and the energy consumption of these deterministic methods by pseudo-randomizing bitstreams. We also propose two novel deterministic methods of processing bitstreams by using low-discrepancy sequences. We further introduce a new advantage to SC paradigm-the skew tolerance of SC circuits. We exploit this advantage in developing polysynchronous clocking, a design strategy for optimizing the clock distribution network of SC systems. Finally, as the first study of its kind to the best of our knowledge, we rethink the memory system design for SC. We propose a seamless stochastic system, StochMem, which features analog memory to trade the energy and area overhead of data conversion for computation accuracy