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

A 16-Channel Fully Configurable Neural SoC With 1.52 μW/Ch Signal Acquisition, 2.79 μW/Ch Real-Time Spike Classifier, and 1.79 TOPS/W Deep Neural Network Accelerator in 22 nm FDSOI

With the advent of high-density micro-electrodes arrays, developing neural probes satisfying the real-time and stringent power-efficiency requirements becomes more challenging. A smart neural probe is an essential device in future neuroscientific research and medical applications. To realize such devices, we present a 22 nm FDSOI SoC with complex on-chip real-time data processing and training for neural signal analysis. It consists of a digitally-assisted 16-channel analog front-end with 1.52 μ W/Ch, dedicated bio-processing accelerators for spike detection and classification with 2.79 μ W/Ch, and a 125 MHz RISC-V CPU, utilizing adaptive body biasing at 0.5 V with a supporting 1.79 TOPS/W MAC array. The proposed SoC shows a proof-of-concept of how to realize a high-level integration of various on-chip accelerators to satisfy the neural probe requirements for modern applications

Analysis and Design of Energy Efficient Frequency Synthesizers for Wireless Integrated Systems

Advances in ultra-low power (ULP) circuit technologies are expanding the IoT applications in our daily life. However, wireless connectivity, small form factor and long lifetime are still the key constraints for many envisioned wearable, implantable and maintenance-free monitoring systems to be practically deployed at a large scale. The frequency synthesizer is one of the most power hungry and complicated blocks that not only constraints RF performance but also offers subtle scalability with power as well. Furthermore, the only indispensable off-chip component, the crystal oscillator, is also associated with the frequency synthesizer as a reference. This thesis addresses the above issues by analyzing how phase noise of the LO affect the frequency modulated wireless system in different aspects and how different noise sources in the PLL affect the performance. Several chip prototypes have been demonstrated including: 1) An ULP FSK transmitter with SAR assisted FLL; 2) A ring oscillator based all-digital BLE transmitter utilizing a quarter RF frequency LO and 4X frequency multiplier; and 3) An XO-less BLE transmitter with an RF reference recovery receiver. The first 2 designs deal with noise sources in the PLL loop for ultimate power and cost reduction, while the third design deals with the reference noise outside the PLL and explores a way to replace the XO in ULP wireless edge nodes. And at last, a comprehensive PN theory is proposed as the design guideline.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/153420/1/chenxing_1.pd

A Biofuel-Cell-Based Energy Harvester With 86% Peak Efficiency and 0.25-V Minimum Input Voltage Using Source-Adaptive MPPT

This article presents an efficient cold-starting energy harvester system, fabricated in 65-nm CMOS. The proposed harvester uses no external electrical components and is compatible with biofuel-cell (BFC) voltage and power ranges. A power-efficient system architecture is proposed to keep the internal circuitry operating at 0.4 V while regulating the output voltage at 1 V using switched-capacitor dc–dc converters and a hysteretic controller. A startup enhancement block is presented to facilitate cold startup with any arbitrary input voltage. A real-time on-chip 2-D maximum power point tracking with source degradation tracing is also implemented to maintain power efficiency maximized over time. The system performs cold startup with a minimum input voltage of 0.39 V and continues its operation if the input voltage degrades to as low as 0.25 V. Peak power efficiency of 86% is achieved at 0.39 V of input voltage and 1.34 μW of output power with 220 nW of average power consumption of the chip. The end-to-end power efficiency is kept above 70% for a wide range of loading powers from 1 to 12 μW. The chip is integrated with a pair of lactate BFC electrodes with 2 mm of diameter on a prototype-printed circuit board (PCB). Integrated operation of the chip with the electrodes and a lactate solution is demonstrated

Towards Very Large Scale Analog (VLSA): Synthesizable Frequency Generation Circuits.

Driven by advancement in integrated circuit design and fabrication technologies, electronic systems have become ubiquitous. This has been enabled powerful digital design tools that continue to shrink the design cost, time-to-market, and the size of digital circuits. Similarly, the manufacturing cost has been constantly declining for the last four decades due to CMOS scaling. However, analog systems have struggled to keep up with the unprecedented scaling of digital circuits. Even today, the majority of the analog circuit blocks are custom designed, do not scale well, and require long design cycles. This thesis analyzes the factors responsible for the slow scaling of analog blocks, and presents a new design methodology that bridges the gap between traditional custom analog design and the modern digital design. The proposed methodology is utilized in implementation of the frequency generation circuits – traditionally considered analog systems. Prototypes covering two different applications were implemented. The first synthesized all-digital phase-locked loop was designed for 400-460 MHz MedRadio applications and was fabricated in a 65 nm CMOS process. The second prototype is an ultra-low power, near-threshold 187-500 kHz clock generator for energy harvesting/autonomous applications. Finally, a digitally-controlled oscillator frequency resolution enhancement technique is presented which allows reduction of quantization noise in ADPLLs without introducing spurs.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/109027/1/mufaisal_1.pd