ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
Displaying 1 - 10 of 90
Description
Radio frequency (RF) transceivers require a disproportionately high effort in terms of test development time, test equipment cost, and test time. The relatively high test cost stems from two contributing factors. First, RF transceivers require the measurement of a diverse set of specifications, requiring multiple test set-ups and long test times, which complicates load-board design, debug, and diagnosis. Second, high frequency operation necessitates the use of expensive equipment, resulting in higher per second test time cost compared with mixed-signal or digital circuits. Moreover, in terms of the non-recurring engineering cost, the need to measure complex specfications complicates the test development process and necessitates a long learning process for test engineers. Test time is dominated by changing and settling time for each test set-up. Thus, single set-up test solutions are desirable. Loop-back configuration where the transmitter output is connected to the receiver input are used as the desirable test set- up for RF transceivers, since it eliminates the reliance on expensive instrumentation for RF signal analysis and enables measuring multiple parameters at once. In-phase and Quadrature (IQ) imbalance, non-linearity, DC offset and IQ time skews are some of the most detrimental imperfections in transceiver performance. Measurement of these parameters in the loop-back mode is challenging due to the coupling between the receiver (RX) and transmitter (TX) parameters. Loop-back based solutions are proposed in this work to resolve this issue. A calibration algorithm for a subset of the above mentioned impairments is also presented. Error Vector Magnitude (EVM) is a system-level parameter that is specified for most advanced communication standards. EVM measurement often takes extensive test development efforts, tester resources, and long test times. EVM is analytically related to system impairments, which are typically measured in a production test i environment. Thus, EVM test can be eliminated from the test list if the relations between EVM and system impairments are derived independent of the circuit implementation and manufacturing process. In this work, the focus is on the WLAN standard, and deriving the relations between EVM and three of the most detrimental impairments for QAM/OFDM based systems (IQ imbalance, non-linearity, and noise). Having low cost test techniques for measuring the RF transceivers imperfections and being able to analytically compute EVM from the measured parameters is a complete test solution for RF transceivers. These techniques along with the proposed calibration method can be used in improving the yield by widening the pass/fail boundaries for transceivers imperfections. For all of the proposed methods, simulation and hardware measurements prove that the proposed techniques provide accurate characterization of RF transceivers.
ContributorsNassery, Afsaneh (Author) / Ozev, Sule (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Kiaei, Sayfe (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2013
Description
Synchronous buck converters have become the obvious choice of design for high efficiency voltage down-conversion applications and find wide scale usage in today's IC industry. The use of digital control in synchronous buck converters is becoming increasingly popular because of its associated advantages over traditional analog counterparts in terms of design flexibility, reduced use of off-chip components, and better programmability to enable advanced controls. They also demonstrate better immunity to noise, enhances tolerance to the process, voltage and temperature (PVT) variations, low chip area and as a result low cost. It enables processing in digital domain requiring a need of analog-digital interfacing circuit viz. Analog to Digital Converter (ADC) and Digital to Analog Converter (DAC). A Digital to Pulse Width Modulator (DPWM) acts as time domain DAC required in the control loop to modulate the ON time of the Power-MOSFETs. The accuracy and efficiency of the DPWM creates the upper limit to the steady state voltage ripple of the DC - DC converter and efficiency in low load conditions. This thesis discusses the prevalent architectures for DPWM in switched mode DC - DC converters. The design of a Hybrid DPWM is presented. The DPWM is 9-bit accurate and is targeted for a Synchronous Buck Converter with a switching frequency of 1.0 MHz. The design supports low power mode(s) for the buck converter in the Pulse Frequency Modulation (PFM) mode as well as other fail-safe features. The design implementation is digital centric making it robust across PVT variations and portable to lower technology nodes. Key target of the design is to reduce design time. The design is tested across large Process (+/- 3σ), Voltage (1.8V +/- 10%) and Temperature (-55.0 °C to 125 °C) and is in the process of tape-out.
ContributorsKumar, Amit (Author) / Bakkaloglu, Bertan (Thesis advisor) / Song, Hongjiang (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2013
Description
Doppler radar can be used to measure respiration and heart rate without contact and through obstacles. In this work, a Doppler radar architecture at 2.4 GHz and a new signal processing algorithm to estimate the respiration and heart rate are presented. The received signal is dominated by the transceiver noise, LO phase noise and clutter which reduces the signal-to-noise ratio of the desired signal. The proposed architecture and algorithm are used to mitigate these issues and obtain an accurate estimate of the heart and respiration rate. Quadrature low-IF transceiver architecture is adopted to resolve null point problem as well as avoid 1/f noise and DC offset due to mixer-LO coupling. Adaptive clutter cancellation algorithm is used to enhance receiver sensitivity coupled with a novel Pattern Search in Noise Subspace (PSNS) algorithm is used to estimate respiration and heart rate. PSNS is a modified MUSIC algorithm which uses the phase noise to enhance Doppler shift detection. A prototype system was implemented using off-the-shelf TI and RFMD transceiver and tests were conduct with eight individuals. The measured results shows accurate estimate of the cardio pulmonary signals in low-SNR conditions and have been tested up to a distance of 6 meters.
ContributorsKhunti, Hitesh Devshi (Author) / Kiaei, Sayfe (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Bliss, Daniel (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2013
Description
This thesis work mainly examined the stability and reliability issues of amorphous Indium Gallium Zinc Oxide (a-IGZO) thin film transistors under bias-illumination stress. Amorphous hydrogenated silicon has been the dominating material used in thin film transistors as a channel layer. However with the advent of modern high performance display technologies, it is required to have devices with better current carrying capability and better reproducibility. This brings the idea of new material for channel layer of these devices. Researchers have tried poly silicon materials, organic materials and amorphous mixed oxide materials as a replacement to conventional amorphous silicon layer. Due to its low price and easy manufacturing process, amorphous mixed oxide thin film transistors have become a viable option to replace the conventional ones in order to achieve high performance display circuits. But with new materials emerging, comes the challenge of reliability and stability issues associated with it. Performance measurement under bias stress and bias-illumination stress have been reported previously. This work proposes novel post processing low temperature long time annealing in optimum ambient in order to annihilate or reduce the defects and vacancies associated with amorphous material which lead to the instability or even the failure of the devices. Thin film transistors of a-IGZO has been tested for standalone illumination stress and bias-illumination stress before and after annealing. HP 4155B semiconductor parameter analyzer has been used to stress the devices and measure the output characteristics and transfer characteristics of the devices. Extra attention has been given about the effect of forming gas annealing on a-IGZO thin film. a-IGZO thin film deposited on silicon substrate has been tested for resistivity, mobility and carrier concentration before and after annealing in various ambient. Elastic Recoil Detection has been performed on the films to measure the amount of hydrogen atoms present in the film. Moreover, the circuit parameters of the thin film transistors has been extracted to verify the physical phenomenon responsible for the instability and failure of the devices. Parameters like channel resistance, carrier mobility, power factor has been extracted and variation of these parameters has been observed before and after the stress.
ContributorsRuhul Hasin, Muhammad (Author) / Alford, Terry L. (Thesis advisor) / Krause, Stephen (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2013
Description
Image resolution limits the extent to which zooming enhances clarity, restricts the size digital photographs can be printed at, and, in the context of medical images, can prevent a diagnosis. Interpolation is the supplementing of known data with estimated values based on a function or model involving some or all of the known samples. The selection of the contributing data points and the specifics of how they are used to define the interpolated values influences how effectively the interpolation algorithm is able to estimate the underlying, continuous signal. The main contributions of this dissertation are three fold: 1) Reframing edge-directed interpolation of a single image as an intensity-based registration problem. 2) Providing an analytical framework for intensity-based registration using control grid constraints. 3) Quantitative assessment of the new, single-image enlargement algorithm based on analytical intensity-based registration. In addition to single image resizing, the new methods and analytical approaches were extended to address a wide range of applications including volumetric (multi-slice) image interpolation, video deinterlacing, motion detection, and atmospheric distortion correction. Overall, the new approaches generate results that more accurately reflect the underlying signals than less computationally demanding approaches and with lower processing requirements and fewer restrictions than methods with comparable accuracy.
ContributorsZwart, Christine M. (Author) / Frakes, David H (Thesis advisor) / Karam, Lina (Committee member) / Kodibagkar, Vikram (Committee member) / Spanias, Andreas (Committee member) / Towe, Bruce (Committee member) / Arizona State University (Publisher)
Created2013
Description
Motion capture using cost-effective sensing technology is challenging and the huge success of Microsoft Kinect has been attracting researchers to uncover the potential of using this technology into computer vision applications. In this thesis, an upper-body motion analysis in a home-based system for stroke rehabilitation using novel RGB-D camera - Kinect is presented. We address this problem by first conducting a systematic analysis of the usability of Kinect for motion analysis in stroke rehabilitation. Then a hybrid upper body tracking approach is proposed which combines off-the-shelf skeleton tracking with a novel depth-fused mean shift tracking method. We proposed several kinematic features reliably extracted from the proposed inexpensive and portable motion capture system and classifiers that correlate torso movement to clinical measures of unimpaired and impaired. Experiment results show that the proposed sensing and analysis works reliably on measuring torso movement quality and is promising for end-point tracking. The system is currently being deployed for large-scale evaluations.
ContributorsDu, Tingfang (Author) / Turaga, Pavan (Thesis advisor) / Spanias, Andreas (Committee member) / Rikakis, Thanassis (Committee member) / Arizona State University (Publisher)
Created2012
Description
Asymptotic and Numerical methods are popular in applied electromagnetism. In this work, the two methods are applied for collimated antennas and calibration targets, respectively. As an asymptotic method, the diffracted Gaussian beam approach (DGBA) is developed for design and simulation of collimated multi-reflector antenna systems, based upon Huygens principle and independent Gaussian beam expansion, referred to as the frames. To simulate a reflector antenna in hundreds to thousands of wavelength, it requires 1E7 - 1E9 independent Gaussian beams. To this end, high performance parallel computing is implemented, based on Message Passing Interface (MPI). The second part of the dissertation includes the plane wave scattering from a target consisting of doubly periodic array of sharp conducting circular cones by the magnetic field integral equation (MFIE) via Coiflet based Galerkin's procedure in conjunction with the Floquet theorem. Owing to the orthogonally, compact support, continuity and smoothness of the Coiflets, well-conditioned impedance matrices are obtained. Majority of the matrix entries are obtained in the spectral domain by one-point quadrature with high precision. For the oscillatory entries, spatial domain computation is applied, bypassing the slow convergence of the spectral summation of the non-damping propagating modes. The simulation results are compared with the solutions from an RWG-MLFMA based commercial software, FEKO, and excellent agreement is observed.
ContributorsWang, Le, 1975- (Author) / Pan, George (Thesis advisor) / Yu, Hongyu (Committee member) / Aberle, James T., 1961- (Committee member) / Diaz, Rodolfo (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2012
Description
Asymptotic comparisons of ergodic channel capacity at high and low signal-to-noise ratios (SNRs) are provided for several adaptive transmission schemes over fading channels with general distributions, including optimal power and rate adaptation, rate adaptation only, channel inversion and its variants. Analysis of the high-SNR pre-log constants of the ergodic capacity reveals the existence of constant capacity difference gaps among the schemes with a pre-log constant of 1. Closed-form expressions for these high-SNR capacity difference gaps are derived, which are proportional to the SNR loss between these schemes in dB scale. The largest one of these gaps is found to be between the optimal power and rate adaptation scheme and the channel inversion scheme. Based on these expressions it is shown that the presence of space diversity or multi-user diversity makes channel inversion arbitrarily close to achieving optimal capacity at high SNR with sufficiently large number of antennas or users. A low-SNR analysis also reveals that the presence of fading provably always improves capacity at sufficiently low SNR, compared to the additive white Gaussian noise (AWGN) case. Numerical results are shown to corroborate our analytical results. This dissertation derives high-SNR asymptotic average error rates over fading channels by relating them to the outage probability, under mild assumptions. The analysis is based on the Tauberian theorem for Laplace-Stieltjes transforms which is grounded on the notion of regular variation, and applies to a wider range of channel distributions than existing approaches. The theory of regular variation is argued to be the proper mathematical framework for finding sufficient and necessary conditions for outage events to dominate high-SNR error rate performance. It is proved that the diversity order being d and the cumulative distribution function (CDF) of the channel power gain having variation exponent d at 0 imply each other, provided that the instantaneous error rate is upper-bounded by an exponential function of the instantaneous SNR. High-SNR asymptotic average error rates are derived for specific instantaneous error rates. Compared to existing approaches in the literature, the asymptotic expressions are related to the channel distribution in a much simpler manner herein, and related with outage more intuitively. The high-SNR asymptotic error rate is also characterized under diversity combining schemes with the channel power gain of each branch having a regularly varying CDF. Numerical results are shown to corroborate our theoretical analysis. This dissertation studies several problems concerning channel inclusion, which is a partial ordering between discrete memoryless channels (DMCs) proposed by Shannon. Specifically, majorization-based conditions are derived for channel inclusion between certain DMCs. Furthermore, under general conditions, channel equivalence defined through Shannon ordering is shown to be the same as permutation of input and output symbols. The determination of channel inclusion is considered as a convex optimization problem, and the sparsity of the weights related to the representation of the worse DMC in terms of the better one is revealed when channel inclusion holds between two DMCs. For the exploitation of this sparsity, an effective iterative algorithm is established based on modifying the orthogonal matching pursuit algorithm. The extension of channel inclusion to continuous channels and its application in ordering phase noises are briefly addressed.
ContributorsZhang, Yuan (Author) / Tepedelenlioğlu, Cihan (Thesis advisor) / Zhang, Junshan (Committee member) / Reisslein, Martin (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2013
Description
Recently, the location of the nodes in wireless networks has been modeled as point processes. In this dissertation, various scenarios of wireless communications in large-scale networks modeled as point processes are considered. The first part of the dissertation considers signal reception and detection problems with symmetric alpha stable noise which is from an interfering network modeled as a Poisson point process. For the signal reception problem, the performance of space-time coding (STC) over fading channels with alpha stable noise is studied. We derive pairwise error probability (PEP) of orthogonal STCs. For general STCs, we propose a maximum-likelihood (ML) receiver, and its approximation. The resulting asymptotically optimal receiver (AOR) does not depend on noise parameters and is computationally simple, and close to the ML performance. Then, signal detection in coexisting wireless sensor networks (WSNs) is considered. We define a binary hypothesis testing problem for the signal detection in coexisting WSNs. For the problem, we introduce the ML detector and simpler alternatives. The proposed mixed-fractional lower order moment (FLOM) detector is computationally simple and close to the ML performance. Stochastic orders are binary relations defined on probability. The second part of the dissertation introduces stochastic ordering of interferences in large-scale networks modeled as point processes. Since closed-form results for the interference distributions for such networks are only available in limited cases, it is of interest to compare network interferences using stochastic. In this dissertation, conditions on the fading distribution and path-loss model are given to establish stochastic ordering between interferences. Moreover, Laplace functional (LF) ordering is defined between point processes and applied for comparing interference. Then, the LF orderings of general classes of point processes are introduced. It is also shown that the LF ordering is preserved when independent operations such as marking, thinning, random translation, and superposition are applied. The LF ordering of point processes is a useful tool for comparing spatial deployments of wireless networks and can be used to establish comparisons of several performance metrics such as coverage probability, achievable rate, and resource allocation even when closed form expressions for such metrics are unavailable.
ContributorsLee, Junghoon (Author) / Tepedelenlioğlu, Cihan (Thesis advisor) / Spanias, Andreas (Committee member) / Reisslein, Martin (Committee member) / Kosut, Oliver (Committee member) / Arizona State University (Publisher)
Created2014
Description
Continuous monitoring of sensor data from smart phones to identify human activities and gestures, puts a heavy load on the smart phone's power consumption. In this research study, the non-Euclidean geometry of the rich sensor data obtained from the user's smart phone is utilized to perform compressive analysis and efficient classification of human activities by employing machine learning techniques. We are interested in the generalization of classical tools for signal approximation to newer spaces, such as rotation data, which is best studied in a non-Euclidean setting, and its application to activity analysis. Attributing to the non-linear nature of the rotation data space, which involve a heavy overload on the smart phone's processor and memory as opposed to feature extraction on the Euclidean space, indexing and compaction of the acquired sensor data is performed prior to feature extraction, to reduce CPU overhead and thereby increase the lifetime of the battery with a little loss in recognition accuracy of the activities. The sensor data represented as unit quaternions, is a more intrinsic representation of the orientation of smart phone compared to Euler angles (which suffers from Gimbal lock problem) or the computationally intensive rotation matrices. Classification algorithms are employed to classify these manifold sequences in the non-Euclidean space. By performing customized indexing (using K-means algorithm) of the evolved manifold sequences before feature extraction, considerable energy savings is achieved in terms of smart phone's battery life.
ContributorsSivakumar, Aswin (Author) / Turaga, Pavan (Thesis advisor) / Spanias, Andreas (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2014