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

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

Power Efficient ADCs for Biomedical Signal Acquisition

Open Access.Peer reviewe

Time-based, Low-power, Low-offset 5-bit 1 GS/s Flash ADC Design in 65nm CMOS Technology

Low-power, medium resolution, high-speed analog-to-digital converters (ADCs) have always been important block which have abundant applications such as digital signal processors (DSP), imaging sensors, environmental and biomedical monitoring devices. This study presents a low power Flash ADC designed in nanometer complementary metal-oxide semiconductors (CMOS) technology. Time analysis on the output delay of the comparators helps to generate one more bit. The proposed technique reduced the power consumption and chip area substantially in comparison to the previous state-of-the-art work. The proposed ADC was developed in TSMC 65nm CMOS technology. The offset cancellation technique was embedded in the proposed comparator to decrement the static offset of the comparator. Moreover, one more bit was generated without using extra comparators. The proposed ADC achieved 4.1 bits ENOB at input Nyquist frequency. The simulated differential and integral non-linearity static tests were equal to +0.26/-0.17 and +0.22/-0.15, respectively. The ADC consumed 7.7 mW at 1 GHz sampling frequency, achieving 415 fJ/Convstep Figure of Merit (FoM)

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

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

LOW-VOLTAGE LOW-POWER ANALOG-TO-DIGITAL CONVERTERS

Ph.DDOCTOR OF PHILOSOPH

Ultra-low power mixed-signal frontend for wearable EEGs

Electronics circuits are ubiquitous in daily life, aided by advancements in the chip design industry, leading to miniaturised solutions for typical day to day problems. One of the critical healthcare areas helped by this advancement in technology is electroencephalography (EEG). EEG is a non-invasive method of tracking a person's brain waves, and a crucial tool in several healthcare contexts, including epilepsy and sleep disorders. Current ambulatory EEG systems still suffer from limitations that affect their usability. Furthermore, many patients admitted to emergency departments (ED) for a neurological disorder like altered mental status or seizures, would remain undiagnosed hours to days after admission, which leads to an elevated rate of death compared to other conditions. Conducting a thorough EEG monitoring in early-stage could prevent further damage to the brain and avoid high mortality. But lack of portability and ease of access results in a long wait time for the prescribed patients. All real signals are analogue in nature, including brainwaves sensed by EEG systems. For converting the EEG signal into digital for further processing, a truly wearable EEG has to have an analogue mixed-signal front-end (AFE). This research aims to define the specifications for building a custom AFE for the EEG recording and use that to review the suitability of the architectures available in the literature. Another critical task is to provide new architectures that can meet the developed specifications for EEG monitoring and can be used in epilepsy diagnosis, sleep monitoring, drowsiness detection and depression study. The thesis starts with a preview on EEG technology and available methods of brainwaves recording. It further expands to design requirements for the AFE, with a discussion about critical issues that need resolving. Three new continuous-time capacitive feedback chopped amplifier designs are proposed. A novel calibration loop for setting the accurate value for a pseudo-resistor, which is a crucial block in the proposed topology, is also discussed. This pseudoresistor calibration loop achieved the resistor variation of under 8.25%. The thesis also presents a new design of a curvature corrected bandgap, as well as a novel DDA based fourth-order Sallen-Key filter. A modified sensor frontend architecture is then proposed, along with a detailed analysis of its implementation. Measurement results of the AFE are finally presented. The AFE consumed a total power of 3.2A (including ADC, amplifier, filter, and current generation circuitry) with the overall integrated input-referred noise of 0.87V-rms in the frequency band of 0.5-50Hz. Measurement results confirmed that only the proposed AFE achieved all defined specifications for the wearable EEG system with the smallest power consumption than state-of-art architectures that meet few but not all specifications. The AFE also achieved a CMRR of 131.62dB, which is higher than any studied architectures.Open Acces

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

Ultra-low Power Circuits for Internet of Things (IOT)

Miniaturized sensor nodes offer an unprecedented opportunity for the semiconductor industry which led to a rapid development of the application space: the Internet of Things (IoT). IoT is a global infrastructure that interconnects physical and virtual things which have the potential to dramatically improve people's daily lives. One of key aspect that makes IoT special is that the internet is expanding into places that has been ever reachable as device form factor continue to decreases. Extremely small sensors can be placed on plants, animals, humans, and geologic features, and connected to the Internet. Several challenges, however, exist that could possibly slow the development of IoT. In this thesis, several circuit techniques as well as system level optimizations to meet the challenging power/energy requirement for the IoT design space are described. First, a fully-integrated temperature sensor for battery-operated, ultra-low power microsystems is presented. Sensor operation is based on temperature independent/dependent current sources that are used with oscillators and counters to generate a digital temperature code. Second, an ultra-low power oscillator designed for wake-up timers in compact wireless sensors is presented. The proposed topology separates the continuous comparator from the oscillation path and activates it only for short period when it is required. As a result, both low power tracking and generation of precise wake-up signal is made possible. Third, an 8-bit sub-ranging SAR ADC for biomedical applications is discussed that takes an advantage of signal characteristics. ADC uses a moving window and stores the previous MSBs voltage value on a series capacitor to achieve energy saving compared to a conventional approach while maintaining its accuracy. Finally, an ultra-low power acoustic sensing and object recognition microsystem that uses frequency domain feature extraction and classification is presented. By introducing ultra-low 8-bit SAR-ADC with 50fF input capacitance, power consumption of the frontend amplifier has been reduced to single digit nW-level. Also, serialized discrete Fourier transform (DFT) feature extraction is proposed in a digital back-end, replacing a high-power/area-consuming conventional FFT.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137157/1/seojeong_1.pd

Energy Harvesting for Self-Powered Wireless Sensors

A wireless sensor system is proposed for a targeted deployment in civil infrastructures (namely bridges) to help mitigate the growing problem of deterioration of civil infrastructures. The sensor motes are self-powered via a novel magnetic shape memory alloy (MSMA) energy harvesting material and a low-frequency, low-power rectifier multiplier (RM). Experimental characterizations of the MSMA device and the RM are presented. A study on practical implementation of a strain gauge sensor and its application in the proposed sensor system are undertaken and a low-power successive approximation register analog-to-digital converter (SAR ADC) is presented. The SAR ADC was fabricated and laboratory characterizations show the proposed low-voltage topology is a viable candidate for deployment in the proposed sensor system. Additionally, a wireless transmitter is proposed to transmit the SAR ADC output using on-off keying (OOK) modulation with an impulse radio ultra-wideband (IR-UWB) transmitter (TX). The RM and SAR ADC were fabricated in ON 0.5 micrometer CMOS process. An alternative transmitter architecture is also presented for use in the 3-10GHz UWB band. Unlike the IR-UWB TX described for the proposed wireless sensor system, the presented transmitter is designed to transfer large amounts of information with little concern for power consumption. This second method of data transmission divides the 3-10GHz spectrum into 528MHz sub-bands and "hops" between these sub-bands during data transmission. The data is sent over these multiple channels for short distances (?3-10m) at data rates over a few hundred million bits per second (Mbps). An UWB TX is presented for implementation in mode-I (3.1-4.6GHz) UWB which utilizes multi-band orthogonal frequency division multiplexing (MB-OFDM) to encode the information. The TX was designed and fabricated using UMC 0.13 micrometer CMOS technology. Measurement results and theoretical system level budgeting are presented for the proposed UWB TX