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- All Subjects: Electrical Engineering
- All Subjects: engineering
- Genre: Doctoral Dissertation
- Creators: Zhang, Yanchao
- Member of: Theses and Dissertations
Description
Thin film transistors (TFTs) are being used in a wide variety of applications such as image sensors, radiation detectors, as well as for use in liquid crystal displays. However, there is a conspicuous absence of interface electronics for bridging the gap between the flexible sensors and digitized displays. Hence is the need to build the same. In this thesis, the feasibility of building mixed analog circuits in TFTs are explored and demonstrated. A flexible CMOS op-amp is demonstrated using a-Si:H and pentacene TFTs. The achieved performance is ¡Ö 50 dB of DC open loop gain with unity gain frequency (UGF) of 7 kHz. The op-amp is built on the popular 2 stage topology with the 2nd stage being cascoded to provide sufficient gain. A novel biasing circuit was successfully developed modifying the gm biasing circuit to retard the performance degradation as the TFTs aged. A switched capacitor 7 bit DAC was developed in only nMOS topology using a-Si:H TFTs, based on charge sharing concept. The DAC achieved a maximum differential non-linearity (DNL) of 0.6 least significant bit (LSB), while the maximum integral non-linearity (INL) was 1 LSB. TFTs were used as switches in this architecture; as a result the performance was quite unchanged even as the TFTs degraded. A 5 bit fully flash ADC was also designed using all nMOS a-Si:H TFTs. Gray coding was implemented at the output to avoid errors due to comparator meta-stability. Finally a 5 bit current steering DAC was also built using all nMOS a-Si:H TFTs. However, due to process variation, the DNL was increased to 1.2 while the INL was about 1.8 LSB. Measurements were made on the external stress effects on zinc indium oxide (ZIO) TFTs. Electrically induced stresses were studied applying DC bias on the gate and drain. These stresses shifted the device characteristics like threshold voltage and mobility. The TFTs were then mechanically stressed by stretching them across cylindrical structures of various radii. Both the subthreshold swing and mobility underwent significant changes when the stress was tensile while the change was minor under compressive stress, applied parallel to channel length.
ContributorsDey, Aritra (Author) / Allee, David R. (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Garrity, Douglas A (Committee member) / Song, Hongjiang (Committee member) / Clark, Lawrence T (Committee member) / Arizona State University (Publisher)
Created2011
Description
CMOS technology is expected to enter the 10nm regime for future integrated circuits (IC). Such aggressive scaling leads to vastly increased variability, posing a grand challenge to robust IC design. Variations in CMOS are often divided into two types: intrinsic variations and process-induced variations. Intrinsic variations are limited by fundamental physics. They are inherent to CMOS structure, considered as one of the ultimate barriers to the continual scaling of CMOS devices. In this work the three primary intrinsic variations sources are studied, including random dopant fluctuation (RDF), line-edge roughness (LER) and oxide thickness fluctuation (OTF). The research is focused on the modeling and simulation of those variations and their scaling trends. Besides the three variations, a time dependent variation source, Random Telegraph Noise (RTN) is also studied. Different from the other three variations, RTN does not contribute much to the total variation amount, but aggregate the worst case of Vth variations in CMOS. In this work a TCAD based simulation study on RTN is presented, and a new SPICE based simulation method for RTN is proposed for time domain circuit analysis. Process-induced variations arise from the imperfection in silicon fabrication, and vary from foundries to foundries. In this work the layout dependent Vth shift due to Rapid-Thermal Annealing (RTA) are investigated. In this work, we develop joint thermal/TCAD simulation and compact modeling tools to analyze performance variability under various layout pattern densities and RTA conditions. Moreover, we propose a suite of compact models that bridge the underlying RTA process with device parameter change for efficient design optimization.
ContributorsYe, Yun, Ph.D (Author) / Cao, Yu (Thesis advisor) / Yu, Hongbin (Committee member) / Song, Hongjiang (Committee member) / Clark, Lawrence (Committee member) / Arizona State University (Publisher)
Created2011
Description
Pulse Density Modulation- (PDM-) based class-D amplifiers can reduce non-linearity and tonal content due to carrier signal in Pulse Width Modulation - (PWM-) based amplifiers. However, their low-voltage analog implementations also require a linear- loop filter and a quantizer. A PDM-based class-D audio amplifier using a frequency-domain quantization is presented in this paper. The digital-intensive frequency domain approach achieves high linearity under low-supply regimes. An analog comparator and a single-bit quantizer are replaced with a Current-Controlled Oscillator- (ICO-) based frequency discriminator. By using the ICO as a phase integrator, a third-order noise shaping is achieved using only two analog integrators. A single-loop, singlebit class-D audio amplifier is presented with an H-bridge switching power stage, which is designed and fabricated on a 0.18 um CMOS process, with 6 layers of metal achieving a total harmonic distortion plus noise (THD+N) of 0.065% and a peak power efficiency of 80% while driving a 4-ohms loudspeaker load. The amplifier can deliver the output power of 280 mW.
ContributorsLee, Junghan (Author) / Bakkaloglu, Bertan (Thesis advisor) / Kiaei, Sayfe (Committee member) / Ozev, Sule (Committee member) / Song, Hongjiang (Committee member) / Arizona State University (Publisher)
Created2011
Description
The cyber-physical systems (CPS) are emerging as the underpinning technology for major industries in the 21-th century. This dissertation is focused on two fundamental issues in cyber-physical systems: network interdependence and information dynamics. It consists of the following two main thrusts. The first thrust is targeted at understanding the impact of network interdependence. It is shown that a cyber-physical system built upon multiple interdependent networks are more vulnerable to attacks since node failures in one network may result in failures in the other network, causing a cascade of failures that would potentially lead to the collapse of the entire infrastructure. There is thus a need to develop a new network science for modeling and quantifying cascading failures in multiple interdependent networks, and to develop network management algorithms that improve network robustness and ensure overall network reliability against cascading failures. To enhance the system robustness, a "regular" allocation strategy is proposed that yields better resistance against cascading failures compared to all possible existing strategies. Furthermore, in view of the load redistribution feature in many physical infrastructure networks, e.g., power grids, a CPS model is developed where the threshold model and the giant connected component model are used to capture the node failures in the physical infrastructure network and the cyber network, respectively. The second thrust is centered around the information dynamics in the CPS. One speculation is that the interconnections over multiple networks can facilitate information diffusion since information propagation in one network can trigger further spread in the other network. With this insight, a theoretical framework is developed to analyze information epidemic across multiple interconnecting networks. It is shown that the conjoining among networks can dramatically speed up message diffusion. Along a different avenue, many cyber-physical systems rely on wireless networks which offer platforms for information exchanges. To optimize the QoS of wireless networks, there is a need to develop a high-throughput and low-complexity scheduling algorithm to control link dynamics. To that end, distributed link scheduling algorithms are explored for multi-hop MIMO networks and two CSMA algorithms under the continuous-time model and the discrete-time model are devised, respectively.
ContributorsQian, Dajun (Author) / Zhang, Junshan (Thesis advisor) / Ying, Lei (Committee member) / Zhang, Yanchao (Committee member) / Cochran, Douglas (Committee member) / Arizona State University (Publisher)
Created2012
Description
Sliding-Mode Control (SMC) has several benefits over traditional Proportional-Integral-Differential (PID) control in terms of fast transient response, robustness to parameter and component variations, and low sensitivity to loop disturbances. An All-Digital Sliding-Mode (ADSM) controlled DC-DC converter, utilizing single-bit oversampled frequency domain digitizers is proposed. In the proposed approach, feedback and reference digitizing Analog-to-Digital Converters (ADC) are based on a single-bit, first order Sigma-Delta frequency to digital converter, running at 32MHz over-sampling rate. The ADSM regulator achieves 1% settling time in less than 5uSec for a load variation of 600mA. The sliding-mode controller utilizes a high-bandwidth hysteretic differentiator and an integrator to perform the sliding control law in digital domain. The proposed approach overcomes the steady state error (or DC offset), and limits the switching frequency range, which are the two common problems associated with sliding-mode controllers. The IC is designed and fabricated on a 0.35um CMOS process occupying an active area of 2.72mm-squared. Measured peak efficiency is 83%.
ContributorsDashtestani, Ahmad (Author) / Bakkaloglu, Bertan (Thesis advisor) / Thornton, Trevor (Committee member) / Song, Hongjiang (Committee member) / Kiaei, Sayfe (Committee member) / Arizona State University (Publisher)
Created2013
Description
The rapid advances in wireless communications and networking have given rise to a number of emerging heterogeneous wireless and mobile networks along with novel networking paradigms, including wireless sensor networks, mobile crowdsourcing, and mobile social networking. While offering promising solutions to a wide range of new applications, their widespread adoption and large-scale deployment are often hindered by people's concerns about the security, user privacy, or both. In this dissertation, we aim to address a number of challenging security and privacy issues in heterogeneous wireless and mobile networks in an attempt to foster their widespread adoption. Our contributions are mainly fivefold. First, we introduce a novel secure and loss-resilient code dissemination scheme for wireless sensor networks deployed in hostile and harsh environments. Second, we devise a novel scheme to enable mobile users to detect any inauthentic or unsound location-based top-k query result returned by an untrusted location-based service providers. Third, we develop a novel verifiable privacy-preserving aggregation scheme for people-centric mobile sensing systems. Fourth, we present a suite of privacy-preserving profile matching protocols for proximity-based mobile social networking, which can support a wide range of matching metrics with different privacy levels. Last, we present a secure combination scheme for crowdsourcing-based cooperative spectrum sensing systems that can enable robust primary user detection even when malicious cognitive radio users constitute the majority.
ContributorsZhang, Rui (Author) / Zhang, Yanchao (Thesis advisor) / Duman, Tolga Mete (Committee member) / Xue, Guoliang (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2013
Description
The rapid advancement of wireless technology has instigated the broad deployment of wireless networks. Different types of networks have been developed, including wireless sensor networks, mobile ad hoc networks, wireless local area networks, and cellular networks. These networks have different structures and applications, and require different control algorithms. The focus of this thesis is to design scheduling and power control algorithms in wireless networks, and analyze their performances. In this thesis, we first study the multicast capacity of wireless ad hoc networks. Gupta and Kumar studied the scaling law of the unicast capacity of wireless ad hoc networks. They derived the order of the unicast throughput, as the number of nodes in the network goes to infinity. In our work, we characterize the scaling of the multicast capacity of large-scale MANETs under a delay constraint D. We first derive an upper bound on the multicast throughput, and then propose a lower bound on the multicast capacity by proposing a joint coding-scheduling algorithm that achieves a throughput within logarithmic factor of the upper bound. We then study the power control problem in ad-hoc wireless networks. We propose a distributed power control algorithm based on the Gibbs sampler, and prove that the algorithm is throughput optimal. Finally, we consider the scheduling algorithm in collocated wireless networks with flow-level dynamics. Specifically, we study the delay performance of workload-based scheduling algorithm with SRPT as a tie-breaking rule. We demonstrate the superior flow-level delay performance of the proposed algorithm using simulations.
ContributorsZhou, Shan (Author) / Ying, Lei (Thesis advisor) / Zhang, Yanchao (Committee member) / Zhang, Junshan (Committee member) / Xue, Guoliang (Committee member) / Arizona State University (Publisher)
Created2013
Description
Data centers connect a larger number of servers requiring IO and switches with low power and delay. Virtualization of IO and network is crucial for these servers, which run virtual processes for computing, storage, and apps. We propose using the PCI Express (PCIe) protocol and a new PCIe switch fabric for IO and switch virtualization. The switch fabric has little data buffering, allowing up to 512 physical 10 Gb/s PCIe2.0 lanes to be connected via a switch fabric. The switch is scalable with adapters running multiple adaptation protocols, such as Ethernet over PCIe, PCIe over Internet, or FibreChannel over Ethernet. Such adaptation protocols allow integration of IO often required for disjoint datacenter applications such as storage and networking. The novel switch fabric based on space-time carrier sensing facilitates high bandwidth, low power, and low delay multi-protocol switching. To achieve Terabit switching, both time (high transmission speed) and space (multi-stage interconnection network) technologies are required. In this paper, we present the design of an up to 256 lanes Clos-network of multistage crossbar switch fabric for PCIe system. The switch core consists of 48 16x16 crossbar sub-switches. We also propose a new output contention resolution algorithm utilizing an out-of-band protocol of Request-To-Send (RTS), Clear-To-Send (CTS) before sending PCIe packets through the switch fabric. Preliminary power and delay estimates are provided.
ContributorsLuo, Haojun (Author) / Hui, Joseph (Thesis advisor) / Song, Hongjiang (Committee member) / Reisslein, Martin (Committee member) / Zhang, Yanchao (Committee member) / Arizona State University (Publisher)
Created2013
Description
Air pollution is one of the biggest challenges people face today. It is closely related to people's health condition. The agencies set up standards to regulate the air pollution. However, many of the pollutants under the regulation level may still result in adverse health effect. On the other hand, it is not clear the exact mechanism of air pollutants and its health effect. So it is difficult for the health centers to advise people how to prevent the air pollutant related diseases. It is of vital importance for both the agencies and the health centers to have a better understanding of the air pollution. Based on these needs, it is crucial to establish mobile health sensors for personal exposure assessment. Here, two sensing principles are illustrated: the tuning fork platform and the colorimetric platform. Mobile devices based on these principles have been built. The detections of ozone, NOX, carbon monoxide and formaldehyde have been shown. An integrated device of nitrogen dioxide and carbon monoxide is introduced. Fan is used for sample delivery instead pump and valves to reduce the size, cost and power consumption. Finally, the future work is discussed.
ContributorsWang, Rui (Author) / Tao, Nongjian (Thesis advisor) / Forzani, Erica (Committee member) / Zhang, Yanchao (Committee member) / Karam, Lina (Committee member) / Arizona State University (Publisher)
Created2012
Description
With the proliferation of mobile computing and Internet-of-Things (IoT), billions of mobile and IoT devices are connected to the Internet, generating zillions of Bytes of data at the network edge. Driving by this trend, there is an urgent need to push the artificial intelligence (AI) frontiers to the network edge to unleash the potential of the edge big data fully. This dissertation aims to comprehensively study collaborative learning and optimization algorithms to build a foundation of edge intelligence. Under this common theme, this dissertation is broadly organized into three parts. The first part of this study focuses on model learning with limited data and limited computing capability at the network edge. A global model initialization is first obtained by running federated learning (FL) across many edge devices, based on which a semi-supervised algorithm is devised for an edge device to carry out quick adaptation, aiming to address the insufficiency of labeled data and to learn a personalized model efficiently. In the second part of this study, collaborative learning between the edge and the cloud is studied to achieve real-time edge intelligence. More specifically, a distributionally robust optimization (DRO) approach is proposed to enable the synergy between local data processing and cloud knowledge transfer. Two attractive uncertainty models are investigated corresponding to the cloud knowledge transfer: the distribution uncertainty set based on the cloud data distribution and the prior distribution of the edge model conditioned on the cloud model. Collaborative learning algorithms are developed along this line. The final part focuses on developing an offline model-based safe Inverse Reinforcement Learning (IRL) algorithm for connected Autonomous Vehicles (AVs). A reward penalty is introduced to penalize unsafe states, and a risk-measure-based approach is proposed to mitigate the model uncertainty introduced by offline training. The experimental results demonstrate the improvement of the proposed algorithm over the existing baselines in terms of cumulative rewards.
ContributorsZhang, Zhaofeng (Author) / Zhang, Junshan (Thesis advisor) / Zhang, Yanchao (Thesis advisor) / Dasarathy, Gautam (Committee member) / Fan, Deliang (Committee member) / Arizona State University (Publisher)
Created2023