A Current-Mode Multi-Channel Integrating Analog-to-Digital Converter

Multi-channel analog to digital converters (ADCs) are required where signals from multiple sensors can be digitized. A lower power per channel for such systems is important in order that when the number of channels is increased the power does not increase drastically. Many applications require signals from current output sensors, such as photosensors and photodiodes to be digitized. Applications for these sensors include spectroscopy and imaging. The ability to digitize current signals without converting currents to voltages saves power, area, and the design time required to implement I-to-V converters. This work describes a novel and unique current-mode multi-channel integrating ADC which processes current signals from sensors and converts it to digital format. The ADC facilitates the processing of current analog signals without the use of transconductors. An attempt has been made also to incorporate voltage-mode techniques into the current-mode design so that the advantages of both techniques can be utilized to augment the performance of the system. Additionally since input signals are in the form of currents, the dynamic range of the ADC is less dependant on the supply voltage. A prototype 4-channel ADC design was fabricated in a 0.5-micron bulk CMOS process. The measurement results for a 10Ksps sampling rate include a DNL, which is less than 0.5 LSB, and a power consumption of less than 2mW per channel

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

A Pipeline Analog-To-Digital Converter for a Plasma Impedance Probe

Space instrumentation technology is an essential tool for rocket and satellite research, and is expected to become popular in commercial and military operations in fields such as radar, imaging, and communications. These instruments are traditionally implemented on printed circuit boards using discrete general-purpose Analog-to-Digital Converter (ADC) devices and other components. A large circuit board is not convenient for use in micro-satellite deployments, where the total payload volume is limited to roughly one cubic foot. Because micro-satellites represent a fast growing trend in satellite research and development, there is motivation to explore miniaturized custom application-specific integrated circuit (ASIC) designs to reduce the volume and power consumption occupied by instrument electronics. In this thesis, a model of a new Plasma Impedance Probe (PIP) architecture, which utilizes a custom-built ADC along with other analog and digital components, is proposed. The model can be fully integrated to produce a low-power, miniaturized impedance probe

Nanopower CMOS transponders for UHF and microwave RFID systems

At first, we present an analysis and a discussion of the design options and tradeoffs for a passive microwave transponder. We derive a set of criteria for the optimization of the voltage multiplier, the power matching network and the backscatter modulator in order to optimize the operating range. In order to match the strictly power requirements, the communication protocol between transponder and reader has been chosen in a convenient way, in order to make the architecture of the passive transponder very simple and then ultra-low-power. From the circuital point of view, the digital section has been implemented in subthreshold CMOS logic with very low supply voltage and clock frequency. We present different solutions to supply power to the transponder, in order to keep the power consumption in the deep sub-µW regime and to drastically reduce the huge sensitivity of the subthreshold logic to temperature and process variations. Moreover, a low-voltage and low-power EEPROM in a standard CMOS process has been implemented. Finally, we have presented the implementation of the entire passive transponder, operating in the UHF or microwave frequency range

Design and debugging of multi-step analog to digital converters

With the fast advancement of CMOS fabrication technology, more and more signal-processing functions are implemented in the digital domain for a lower cost, lower power consumption, higher yield, and higher re-configurability. The trend of increasing integration level for integrated circuits has forced the A/D converter interface to reside on the same silicon in complex mixed-signal ICs containing mostly digital blocks for DSP and control. However, specifications of the converters in various applications emphasize high dynamic range and low spurious spectral performance. It is nontrivial to achieve this level of linearity in a monolithic environment where post-fabrication component trimming or calibration is cumbersome to implement for certain applications or/and for cost and manufacturability reasons. Additionally, as CMOS integrated circuits are accomplishing unprecedented integration levels, potential problems associated with device scaling – the short-channel effects – are also looming large as technology strides into the deep-submicron regime. The A/D conversion process involves sampling the applied analog input signal and quantizing it to its digital representation by comparing it to reference voltages before further signal processing in subsequent digital systems. Depending on how these functions are combined, different A/D converter architectures can be implemented with different requirements on each function. Practical realizations show the trend that to a first order, converter power is directly proportional to sampling rate. However, power dissipation required becomes nonlinear as the speed capabilities of a process technology are pushed to the limit. Pipeline and two-step/multi-step converters tend to be the most efficient at achieving a given resolution and sampling rate specification. This thesis is in a sense unique work as it covers the whole spectrum of design, test, debugging and calibration of multi-step A/D converters; it incorporates development of circuit techniques and algorithms to enhance the resolution and attainable sample rate of an A/D converter and to enhance testing and debugging potential to detect errors dynamically, to isolate and confine faults, and to recover and compensate for the errors continuously. The power proficiency for high resolution of multi-step converter by combining parallelism and calibration and exploiting low-voltage circuit techniques is demonstrated with a 1.8 V, 12-bit, 80 MS/s, 100 mW analog to-digital converter fabricated in five-metal layers 0.18-µm CMOS process. Lower power supply voltages significantly reduce noise margins and increase variations in process, device and design parameters. Consequently, it is steadily more difficult to control the fabrication process precisely enough to maintain uniformity. Microscopic particles present in the manufacturing environment and slight variations in the parameters of manufacturing steps can all lead to the geometrical and electrical properties of an IC to deviate from those generated at the end of the design process. Those defects can cause various types of malfunctioning, depending on the IC topology and the nature of the defect. To relive the burden placed on IC design and manufacturing originated with ever-increasing costs associated with testing and debugging of complex mixed-signal electronic systems, several circuit techniques and algorithms are developed and incorporated in proposed ATPG, DfT and BIST methodologies. Process variation cannot be solved by improving manufacturing tolerances; variability must be reduced by new device technology or managed by design in order for scaling to continue. Similarly, within-die performance variation also imposes new challenges for test methods. With the use of dedicated sensors, which exploit knowledge of the circuit structure and the specific defect mechanisms, the method described in this thesis facilitates early and fast identification of excessive process parameter variation effects. The expectation-maximization algorithm makes the estimation problem more tractable and also yields good estimates of the parameters for small sample sizes. To allow the test guidance with the information obtained through monitoring process variations implemented adjusted support vector machine classifier simultaneously minimize the empirical classification error and maximize the geometric margin. On a positive note, the use of digital enhancing calibration techniques reduces the need for expensive technologies with special fabrication steps. Indeed, the extra cost of digital processing is normally affordable as the use of submicron mixed signal technologies allows for efficient usage of silicon area even for relatively complex algorithms. Employed adaptive filtering algorithm for error estimation offers the small number of operations per iteration and does not require correlation function calculation nor matrix inversions. The presented foreground calibration algorithm does not need any dedicated test signal and does not require a part of the conversion time. It works continuously and with every signal applied to the A/D converter. The feasibility of the method for on-line and off-line debugging and calibration has been verified by experimental measurements from the silicon prototype fabricated in standard single poly, six metal 0.09-µm CMOS process

Algorithm/Architecture Co-Design for Low-Power Neuromorphic Computing

The development of computing systems based on the conventional von Neumann architecture has slowed down in the past decade as complementary metal-oxide-semiconductor (CMOS) technology scaling becomes more and more difficult. To satisfy the ever-increasing demands in computing power, neuromorphic computing has emerged as an attractive alternative. This dissertation focuses on developing learning algorithm, hardware architecture, circuit components, and design methodologies for low-power neuromorphic computing that can be employed in various energy-constrained applications. A top-down approach is adopted in this research. Starting from the algorithm-architecture co-design, a hardware-friendly learning algorithm is developed for spiking neural networks (SNNs). The possibility of estimating gradients from spike timings is explored. The learning algorithm is developed for the ease of hardware implementation, as well as the compatibility with many well-established learning techniques developed for classic artificial neural networks (ANNs). An SNN hardware equipped with the proposed on-chip learning algorithm is implemented in CMOS technology. In this design, two unique features of SNNs, the event-driven computation and the inferring with a progressive precision, are leveraged to reduce the energy consumption. In addition to low-power SNN hardware, accelerators for ANNs are also presented to accelerate the adaptive dynamic programing algorithm. An efficient and flexible single-instruction-multiple-data architecture is proposed to exploit the inherent data-level parallelism in the inference and learning of ANNs. In addition, the accelerator is augmented with a virtual update technique, which helps improve the throughput and energy efficiency remarkably. Lastly, two techniques in the architecture-circuit level are introduced to mitigate the degraded reliability of the memory system in a neuromorphic hardware owing to the aggressively-scaled supply voltage and integration density. The first method uses on-chip feedback to compensate for the process variation and the second technique improves the throughput and energy efficiency of a conventional error-correction method.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144149/1/zhengn_1.pd

Impact of atomistic device variability on analogue circuit design

Scaling of complementary metal-oxide-semiconductor (CMOS) technology has benefited the semiconductor industry for almost half a century. For CMOS devices with a physical gate-length in the sub-100 nm range, extreme device variability is introduced and has become a major stumbling block for next generation analogue circuit design. Both opportunities and challenges have therefore confronted analogue circuit designers. Small geometry device can enable high-speed analogue circuit designs, such as data conversion interfaces that can work in the radio frequency range. These designs can be co-integrated with digital systems to achieve low cost, high-performance, single-chip solutions that could only be achieved using multi-chip solutions in the past. However, analogue circuit designs are extremely vulnerable to device mismatch, since a large number of symmetric transistor pairs and circuit cells are required. The increase in device variability from sub-100 nm processes has therefore significantly reduced the production yield of the conventional designs. Mismatch models have been developed to analytically evaluate the magnitude of random variations. Based on measurements from custom designed test structures, the statistics of process variation can be estimated using design related parameters. However, existing models can no longer accurately estimate the magnitude of mismatch for sub-100 nm “atomistic” devices, since short-channel effects have become important. In this thesis, a new mismatch model for small geometry devices will be proposed to address this problem. Based on knowledge of the matching performance obtained from the mismatch model, design solutions are desired at different design levels for a variety of circuit topologies. In this thesis, transistor level compensation solutions have been investigated and closed-loop compensation circuits have been proposed. At circuit level, a latch-based comparator has been used to develop a compensation solution because this type of comparator is extremely sensitive to the device mismatch. These comparators are also used as the fundamental building block for the analogue-to-digital converters (ADC). The proposed comparator compensation scheme is used to improve the performance of a high-speed flash ADC

An offset auto-calibration technique with cost-effective implementation for comparator and operational amplifier

Comparators are one of the most fundamental building blocks in all electronic systems involving analog and digital information. A comparator’s performance, or the accuracy of its output, is determined by the comparator’s offset voltage, which includes random offset and systematic offset. To guarantee the overall performance of an entire electronic system, offset-trimming techniques are often necessary to reduce inaccuracy. This study analyzes the offset errors in a representative comparator structure and describes an auto-calibration technique to systematically and significantly reducing the offset. The auto-calibration technique involves trimming of the comparator input transistor pair. Various trimming-switch structures are considered and compared, such as constant-sized drain switch (CDS), constant-sized gate switch (CGS), constant-sized source switch (CSS), binary-weighted source switch (BSS), and constant size split-source switch (SSS). The comparator and the offset auto-calibration circuits are designed using the GlobalFoundry 0.13μm process. Then an offset trimming algorithm, which is written on MATLAB, is applied to these circuits. Afterwards, the results are collected and analyzed. A comparison of linearity and trimming range (TR) achieved with different trimming switch structures is performed to demonstrate advantages and disadvantages of each switch scheme. The results are also plotted in a histogram to show the normal distribution of each scheme. Finally, offset cancellation technique is implemented in an operational amplifier (Op Amp) circuit with further analysis and comparison to prove the methodology