Ultra-Low Power Circuit Design for Miniaturized IoT Platform

This thesis examines the ultra-low power circuit techniques for mm-scale Internet of Things (IoT) platforms. The IoT devices are known for their small form factors and limited battery capacity and lifespan. So, ultra-low power consumption of always-on blocks is required for the IoT devices that adopt aggressive duty-cycling for high power efficiency and long lifespan. Several problems need to be addressed regarding IoT device designs, such as ultra-low power circuit design techniques for sleep mode and energy-efficient and fast data rate transmission for active mode communication. Therefore, this thesis highlights the ultra-low power always-on systems, focusing on energy efficient optical transmission in order to miniaturize the IoT systems. First, this thesis presents a battery-less sub-nW micro-controller for an always-operating system implemented with a newly proposed logic family. Second, it proposes an always-operating sub-nW light-to-digital converter to measure instant light intensity and cumulative light exposure, which employs the characteristics of this proposed logic family. Third, it presents an ultra-low standby power optical wake-up receiver with ambient light canceling using dual-mode operation. Finally, an energy-efficient low power optical transmitter for an implantable IoT device is suggested. Implications for future research are also provided.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/145862/1/imhotep_1.pd

Toward a Flying MEMS Robot

The work in this thesis includes the design, modeling, and testing of motors and rotor blades to be used on a millimeter-scale helicopter style flying micro air vehicle (MAV). Three different types of motor designs were developed and tested, which included circular scratch drives, electrostatic motors, and comb drive resonators. Six different rotor designs were tested; five used residual stress while one design used photoresist to act as a hinge to achieve rotor blade deflection. Two key parameters of performance were used to evaluate the motor and rotor blade designs: the frequency of motor rotation and the angle of deflection achieved in the rotor blades. One successful design utilized a scratch drive motor with four attached rotor blades to try to achieve lift. While the device rotated successfully, the rotational frequency was insufficient to achieve lift-off. The electrostatic motor designs proved to be a challenge, only briefly moving before shorting out; nonetheless, lessons were learned. Comb drive designs operated over a wide range of high frequencies, lending them to be a promising method of turning a rotary MAV. None of the fabricated devices were able to achieve lift, due to insufficient rotational rates and low angles of attack on the rotor blades. With slight modifications to the current designs, the required rotational rates and rotor blade deflections would yield a viable MAV. The ultimate objective of this effort was to create an autonomous MAV on the millimeter scale, able to sense and act upon targets in its environment. Such a craft would be virtually undetectable, stealthily maneuvering and capable of precision engagement

Millimeter-Scale and Energy-Efficient RF Wireless System

This dissertation focuses on energy-efficient RF wireless system with millimeter-scale dimension, expanding the potential use cases of millimeter-scale computing devices. It is challenging to develop RF wireless system in such constrained space. First, millimeter-sized antennae are electrically-small, resulting in low antenna efficiency. Second, their energy source is very limited due to the small battery and/or energy harvester. Third, it is required to eliminate most or all off-chip devices to further reduce system dimension. In this dissertation, these challenges are explored and analyzed, and new methods are proposed to solve them. Three prototype RF systems were implemented for demonstration and verification. The first prototype is a 10 cubic-mm inductive-coupled radio system that can be implanted through a syringe, aimed at healthcare applications with constrained space. The second prototype is a 3x3x3 mm far-field 915MHz radio system with 20-meter NLOS range in indoor environment. The third prototype is a low-power BLE transmitter using 3.5x3.5 mm planar loop antenna, enabling millimeter-scale sensors to connect with ubiquitous IoT BLE-compliant devices. The work presented in this dissertation improves use cases of millimeter-scale computers by presenting new methods for improving energy efficiency of wireless radio system with extremely small dimensions. The impact is significant in the age of IoT when everything will be connected in daily life.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/147686/1/yaoshi_1.pd

Ultra-Low Power Optical Interface Circuits for Nearly Invisible Wireless Sensor Nodes.

Technological advances in the semiconductor industry and integrated circuit design have resulted in electronic devices that are smaller and cheaper than ever, and yet they are more pervasive and powerful than what could hardly be imagined several decades ago. Nowadays, small hand-held devices such as smartphones have completely reshaped the way people communicate, share information, and get entertained. According to Bell’s Law, the next generation of computers will be cubic-millimeter-scale in volume with more prevalent presence than any other computing platform available today, opening up myriad of new applications. In this dissertation, a millimeter-scale wireless sensor node for visual sensing applications is proposed, with emphasis on the optical interface circuits that enable wireless optical communication and visual imaging. Visual monitoring and imaging with CMOS image sensors opens up a variety of new applications for wireless sensor nodes, ranging from surveillance to in vivo molecular imaging. In particular, the ability to detect motion can enable intelligent power management through on-demand duty cycling and reduce the data storage requirement. Optical communication provides an ultra-low power method to wirelessly control or transmit data to the sensor node after encapsulation and deployment. The proposed wireless sensor node is a nearly-invisible, yet a complete system with imaging, optics, two-way wireless communication, CPU, memory, battery and energy harvesting with solar cells. During its ultra-low power motion detection mode, the overall power consumption is merely 304 nW, allowing energy autonomous continuous operation with 10 klux of background lighting. Such complete features in the unprecedented form factor can revolutionize the role of electronics in our future daily lives, taking the “Smart Dust” concept from fiction to reality.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/110399/1/coolkgh_1.pd

Power Management and SRAM for Energy-Autonomous and Low-Power Systems

We demonstrate the two first-known, complete, self-powered millimeter-scale computer systems. These microsystems achieve zero-net-energy operation using solar energy harvesting and ultra-low-power circuits. A medical implant for monitoring intraocular pressure (IOP) is presented as part of a treatment for glaucoma. The 1.5mm3 IOP monitor is easily implantable because of its small size and measures IOP with 0.5mmHg accuracy. It wirelessly transmits data to an external wand while consuming 4.7nJ/bit. This provides rapid feedback about treatment efficacies to decrease physician response time and potentially prevent unnecessary vision loss. A nearly-perpetual temperature sensor is presented that processes data using a 2.1μW near-threshold ARM°R Cortex- M3TM μP that provides a widely-used and trusted programming platform. Energy harvesting and power management techniques for these two microsystems enable energy-autonomous operation. The IOP monitor harvests 80nW of solar power while consuming only 5.3nW, extending lifetime indefinitely. This allows the device to provide medical information for extended periods of time, giving doctors time to converge upon the best glaucoma treatment. The temperature sensor uses on-demand power delivery to improve low-load dc-dc voltage conversion efficiency by 4.75x. It also performs linear regulation to deliver power with low noise, improved load regulation, and tight line regulation. Low-power high-throughput SRAM techniques help millimeter-scale microsystems meet stringent power budgets. VDD scaling in memory decreases energy per access, but also decreases stability margins. These margins can be improved using sizing, VTH selection, and assist circuits, as well as new bitcell designs. Adaptive Crosshairs modulation of SRAM power supplies fixes 70% of parametric failures. Half-differential SRAM design improves stability, reducing VMIN by 72mV. The circuit techniques for energy autonomy presented in this dissertation enable millimeter-scale microsystems for medical implants, such as blood pressure and glucose sensors, as well as non-medical applications, such as supply chain and infrastructure monitoring. These pervasive sensors represent the continuation of Bell’s Law, which accurately traces the evolution of computers as they become smaller, more numerous, and more powerful. The development of millimeter-scale massively-deployed ubiquitous computers ensures the continued expansion and profitability of the semiconductor industry. NanoWatt circuit techniques will allow us to meet this next frontier in IC design.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/86387/1/grgkchen_1.pd

Designing Flexible, Energy Efficient and Secure Wireless Solutions for the Internet of Things

The Internet of Things (IoT) is an emerging concept where ubiquitous physical objects (things) consisting of sensor, transceiver, processing hardware and software are interconnected via the Internet. The information collected by individual IoT nodes is shared among other often heterogeneous devices and over the Internet. This dissertation presents flexible, energy efficient and secure wireless solutions in the IoT application domain. System design and architecture designs are discussed envisioning a near-future world where wireless communication among heterogeneous IoT devices are seamlessly enabled. Firstly, an energy-autonomous wireless communication system for ultra-small, ultra-low power IoT platforms is presented. To achieve orders of magnitude energy efficiency improvement, a comprehensive system-level framework that jointly optimizes various system parameters is developed. A new synchronization protocol and modulation schemes are specified for energy-scarce ultra-small IoT nodes. The dynamic link adaptation is proposed to guarantee the ultra-small node to always operate in the most energy efficiency mode, given an operating scenario. The outcome is a truly energy-optimized wireless communication system to enable various new applications such as implanted smart-dust devices. Secondly, a configurable Software Defined Radio (SDR) baseband processor is designed and shown to be an efficient platform on which to execute several IoT wireless standards. It is a custom SIMD execution model coupled with a scalar unit and several architectural optimizations: streaming registers, variable bitwidth, dedicated ALUs, and an optimized reduction network. Voltage scaling and clock gating are employed to further reduce the power, with a more than a 100% time margin reserved for reliable operation in the near-threshold region. Two upper bound systems are evaluated. A comprehensive power/area estimation indicates that the overhead of realizing SDR flexibility is insignificant. The benefit of baseband SDR is quantified and evaluated. To further augment the benefits of a flexible baseband solution and to address the security issue of IoT connectivity, a light-weight Galois Field (GF) processor is proposed. This processor enables both energy-efficient block coding and symmetric/asymmetric cryptography kernel processing for a wide range of GF sizes (2^m, m = 2, 3, ..., 233) and arbitrary irreducible polynomials. Program directed connections among primitive GF arithmetic units enable dynamically configured parallelism to efficiently perform either four-way SIMD GF operations, including multiplicative inverse, or a long bit-width GF product in a single cycle. This demonstrates the feasibility of a unified architecture to enable error correction coding flexibility and secure wireless communication in the low power IoT domain.PHDComputer Science & EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137164/1/yajchen_1.pd

Photovoltaic Energy Harvesting for Millimeter-Scale Systems

The Internet of Things (IoT) based on mm-scale sensors is a transformational technology that opens up new capabilities for biomedical devices, surveillance, micro-robots and industrial monitoring. Energy harvesting approaches to power IoT have traditionally included thermal, vibration and radio frequency. However, the achievement of efficient energy scavenging for IoT at the mm-scale or sub mm-scale has been elusive. In this work, I show that photovoltaic (PV) cells at the mm-scale can be an alternative means of wireless power transfer to mm-scale sensors for IoT, utilizing ambient indoor lighting or intentional irradiation of near-infrared (NIR) LED sources through biological tissue. Single silicon and GaAs photovoltaic cells at the mm-scale can achieve a power conversion efficiency of more than 17 % for silicon and 30 % for GaAs under low-flux NIR irradiation at 850 nm through the optimized device structure and sidewall/surface passivation studies, which guarantees perpetual operation of mm-scale sensors. Furthermore, monolithic single-junction GaAs photovoltaic modules offer a means for series-interconnected cells to provide sufficient voltage (> 5 V) for direct battery charging, and bypassing needs for voltage up-conversion circuitry. However, there is a continuing challenge to miniaturize such PV systems down to the sub mm-scale with minimal optical losses from device isolation and metal interconnects and efficient voltage up-conversion. Vertically stacked dual-junction PV cells and modules are demonstrated to increase the output voltage per cell and minimize area losses for direct powering of miniature devices for IoT and bio-implantable applications with low-irradiance narrowband spectral illumination. Dual-junction PV cells at small dimensions (150 µm x 150 µm) demonstrate power conversion efficiency greater than 22 % with more than 1.2 V output voltage under low-flux 850 nm NIR LED illumination, which is sufficient for batteryless operation of miniaturized CMOS IC chips. The output voltage of dual-junction PV modules with eight series-connected single cells is greater than 10 V while maintaining an efficiency of more than 18 %. Finally, I demonstrate monolithic PV/LED modules at the µm-scale for brain-machine interfaces, enabling two-way optical power and data transfer in a through-tissue configuration. The wafer-level assembly plan for the 3D vertical integration of three different systems including GaAs LED/PV modules, CMOS silicon chips, and neural probes is proposed.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/163261/1/esmoon_1.pd

Ultra-Low Power Circuit Design for Cubic-Millimeter Wireless Sensor Platform.

Modern daily life is surrounded by smaller and smaller computing devices. As Bell’s Law predicts, the research community is now looking at tiny computing platforms and mm3-scale sensor systems are drawing an increasing amount of attention since they can create a whole new computing environment. Designing mm3-scale sensor nodes raises various circuit and system level challenges and we have addressed and proposed novel solutions for many of these challenges to create the first complete 1.0mm3 sensor system including a commercial microprocessor. We demonstrate a 1.0mm3 form factor sensor whose modular die-stacked structure allows maximum volume utilization. Low power I2C communication enables inter-layer serial communication without losing compatibility to standard I2C communication protocol. A dual microprocessor enables concurrent computation for the sensor node control and measurement data processing. A multi-modal power management unit allowed energy harvesting from various harvesting sources. An optical communication scheme is provided for initial programming, synchronization and re-programming after recovery from battery discharge. Standby power reduction techniques are investigated and a super cut-off power gating scheme with an ultra-low power charge pump reduces the standby power of logic circuits by 2-19× and memory by 30%. Different approaches for designing low-power memory for mm3-scale sensor nodes are also presented in this work. A dual threshold voltage gain cell eDRAM design achieves the lowest eDRAM retention power and a 7T SRAM design based on hetero-junction tunneling transistors reduces the standby power of SRAM by 9-19× with only 15% area overhead. We have paid special attention to the timer for the mm3-scale sensor systems and propose a multi-stage gate-leakage-based timer to limit the standard deviation of the error in hourly measurement to 196ms and a temperature compensation scheme reduces temperature dependency to 31ppm/°C. These techniques for designing ultra-low power circuits for a mm3-scale sensor enable implementation of a 1.0mm3 sensor node, which can be used as a skeleton for future micro-sensor systems in variety of applications. These microsystems imply the continuation of the Bell’s Law, which also predicts the massive deployment of mm3-scale computing systems and emergence of even smaller and more powerful computing systems in the near future.Ph.D.Electrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91438/1/sori_1.pd

Living IoT: A Flying Wireless Platform on Live Insects

Sensor networks with devices capable of moving could enable applications ranging from precision irrigation to environmental sensing. Using mechanical drones to move sensors, however, severely limits operation time since flight time is limited by the energy density of current battery technology. We explore an alternative, biology-based solution: integrate sensing, computing and communication functionalities onto live flying insects to create a mobile IoT platform. Such an approach takes advantage of these tiny, highly efficient biological insects which are ubiquitous in many outdoor ecosystems, to essentially provide mobility for free. Doing so however requires addressing key technical challenges of power, size, weight and self-localization in order for the insects to perform location-dependent sensing operations as they carry our IoT payload through the environment. We develop and deploy our platform on bumblebees which includes backscatter communication, low-power self-localization hardware, sensors, and a power source. We show that our platform is capable of sensing, backscattering data at 1 kbps when the insects are back at the hive, and localizing itself up to distances of 80 m from the access points, all within a total weight budget of 102 mg.Comment: Co-primary authors: Vikram Iyer, Rajalakshmi Nandakumar, Anran Wang, In Proceedings of Mobicom. ACM, New York, NY, USA, 15 pages, 201