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 78
151690-Thumbnail Image.png
Description
Practical communication systems are subject to errors due to imperfect time alignment among the communicating nodes. Timing errors can occur in different forms depending on the underlying communication scenario. This doctoral study considers two different classes of asynchronous systems; point-to-point (P2P) communication systems with synchronization errors, and asynchronous cooperative systems.

Practical communication systems are subject to errors due to imperfect time alignment among the communicating nodes. Timing errors can occur in different forms depending on the underlying communication scenario. This doctoral study considers two different classes of asynchronous systems; point-to-point (P2P) communication systems with synchronization errors, and asynchronous cooperative systems. In particular, the focus is on an information theoretic analysis for P2P systems with synchronization errors and developing new signaling solutions for several asynchronous cooperative communication systems. The first part of the dissertation presents several bounds on the capacity of the P2P systems with synchronization errors. First, binary insertion and deletion channels are considered where lower bounds on the mutual information between the input and output sequences are computed for independent uniformly distributed (i.u.d.) inputs. Then, a channel suffering from both synchronization errors and additive noise is considered as a serial concatenation of a synchronization error-only channel and an additive noise channel. It is proved that the capacity of the original channel is lower bounded in terms of the synchronization error-only channel capacity and the parameters of both channels. On a different front, to better characterize the deletion channel capacity, the capacity of three independent deletion channels with different deletion probabilities are related through an inequality resulting in the tightest upper bound on the deletion channel capacity for deletion probabilities larger than 0.65. Furthermore, the first non-trivial upper bound on the 2K-ary input deletion channel capacity is provided by relating the 2K-ary input deletion channel capacity with the binary deletion channel capacity through an inequality. The second part of the dissertation develops two new relaying schemes to alleviate asynchronism issues in cooperative communications. The first one is a single carrier (SC)-based scheme providing a spectrally efficient Alamouti code structure at the receiver under flat fading channel conditions by reducing the overhead needed to overcome the asynchronism and obtain spatial diversity. The second one is an orthogonal frequency division multiplexing (OFDM)-based approach useful for asynchronous cooperative systems experiencing excessive relative delays among the relays under frequency-selective channel conditions to achieve a delay diversity structure at the receiver and extract spatial diversity.
ContributorsRahmati, Mojtaba (Author) / Duman, Tolga M. (Thesis advisor) / Zhang, Junshan (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Reisslein, Martin (Committee member) / Arizona State University (Publisher)
Created2013
152113-Thumbnail Image.png
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

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
152260-Thumbnail Image.png
Description
Autonomous vehicle control systems utilize real-time kinematic Global Navigation Satellite Systems (GNSS) receivers to provide a position within two-centimeter of truth. GNSS receivers utilize the satellite signal time of arrival estimates to solve for position; and multipath corrupts the time of arrival estimates with a time-varying bias. Time of arrival

Autonomous vehicle control systems utilize real-time kinematic Global Navigation Satellite Systems (GNSS) receivers to provide a position within two-centimeter of truth. GNSS receivers utilize the satellite signal time of arrival estimates to solve for position; and multipath corrupts the time of arrival estimates with a time-varying bias. Time of arrival estimates are based upon accurate direct sequence spread spectrum (DSSS) code and carrier phase tracking. Current multipath mitigating GNSS solutions include fixed radiation pattern antennas and windowed delay-lock loop code phase discriminators. A new multipath mitigating code tracking algorithm is introduced that utilizes a non-symmetric correlation kernel to reject multipath. Independent parameters provide a means to trade-off code tracking discriminant gain against multipath mitigation performance. The algorithm performance is characterized in terms of multipath phase error bias, phase error estimation variance, tracking range, tracking ambiguity and implementation complexity. The algorithm is suitable for modernized GNSS signals including Binary Phase Shift Keyed (BPSK) and a variety of Binary Offset Keyed (BOC) signals. The algorithm compensates for unbalanced code sequences to ensure a code tracking bias does not result from the use of asymmetric correlation kernels. The algorithm does not require explicit knowledge of the propagation channel model. Design recommendations for selecting the algorithm parameters to mitigate precorrelation filter distortion are also provided.
ContributorsMiller, Steven (Author) / Spanias, Andreas (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Tsakalis, Konstantinos (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2013
151982-Thumbnail Image.png
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

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
151971-Thumbnail Image.png
Description
Electrical neural activity detection and tracking have many applications in medical research and brain computer interface technologies. In this thesis, we focus on the development of advanced signal processing algorithms to track neural activity and on the mapping of these algorithms onto hardware to enable real-time tracking. At the heart

Electrical neural activity detection and tracking have many applications in medical research and brain computer interface technologies. In this thesis, we focus on the development of advanced signal processing algorithms to track neural activity and on the mapping of these algorithms onto hardware to enable real-time tracking. At the heart of these algorithms is particle filtering (PF), a sequential Monte Carlo technique used to estimate the unknown parameters of dynamic systems. First, we analyze the bottlenecks in existing PF algorithms, and we propose a new parallel PF (PPF) algorithm based on the independent Metropolis-Hastings (IMH) algorithm. We show that the proposed PPF-IMH algorithm improves the root mean-squared error (RMSE) estimation performance, and we demonstrate that a parallel implementation of the algorithm results in significant reduction in inter-processor communication. We apply our implementation on a Xilinx Virtex-5 field programmable gate array (FPGA) platform to demonstrate that, for a one-dimensional problem, the PPF-IMH architecture with four processing elements and 1,000 particles can process input samples at 170 kHz by using less than 5% FPGA resources. We also apply the proposed PPF-IMH to waveform-agile sensing to achieve real-time tracking of dynamic targets with high RMSE tracking performance. We next integrate the PPF-IMH algorithm to track the dynamic parameters in neural sensing when the number of neural dipole sources is known. We analyze the computational complexity of a PF based method and propose the use of multiple particle filtering (MPF) to reduce the complexity. We demonstrate the improved performance of MPF using numerical simulations with both synthetic and real data. We also propose an FPGA implementation of the MPF algorithm and show that the implementation supports real-time tracking. For the more realistic scenario of automatically estimating an unknown number of time-varying neural dipole sources, we propose a new approach based on the probability hypothesis density filtering (PHDF) algorithm. The PHDF is implemented using particle filtering (PF-PHDF), and it is applied in a closed-loop to first estimate the number of dipole sources and then their corresponding amplitude, location and orientation parameters. We demonstrate the improved tracking performance of the proposed PF-PHDF algorithm and map it onto a Xilinx Virtex-5 FPGA platform to show its real-time implementation potential. Finally, we propose the use of sensor scheduling and compressive sensing techniques to reduce the number of active sensors, and thus overall power consumption, of electroencephalography (EEG) systems. We propose an efficient sensor scheduling algorithm which adaptively configures EEG sensors at each measurement time interval to reduce the number of sensors needed for accurate tracking. We combine the sensor scheduling method with PF-PHDF and implement the system on an FPGA platform to achieve real-time tracking. We also investigate the sparsity of EEG signals and integrate compressive sensing with PF to estimate neural activity. Simulation results show that both sensor scheduling and compressive sensing based methods achieve comparable tracking performance with significantly reduced number of sensors.
ContributorsMiao, Lifeng (Author) / Chakrabarti, Chaitali (Thesis advisor) / Papandreou-Suppappola, Antonia (Thesis advisor) / Zhang, Junshan (Committee member) / Bliss, Daniel (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2013
151542-Thumbnail Image.png
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

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
152315-Thumbnail Image.png
Description
ABSTRACT Whole genome sequencing (WGS) and whole exome sequencing (WES) are two comprehensive genomic tests which use next-generation sequencing technology to sequence most of the 3.2 billion base pairs in a human genome (WGS) or many of the estimated 22,000 protein-coding genes in the genome (WES). The promises offered from

ABSTRACT Whole genome sequencing (WGS) and whole exome sequencing (WES) are two comprehensive genomic tests which use next-generation sequencing technology to sequence most of the 3.2 billion base pairs in a human genome (WGS) or many of the estimated 22,000 protein-coding genes in the genome (WES). The promises offered from WGS/WES are: to identify suspected yet unidentified genetic diseases, to characterize the genomic mutations in a tumor to identify targeted therapeutic agents and, to predict future diseases with the hope of promoting disease prevention strategies and/or offering early treatment. Promises notwithstanding, sequencing a human genome presents several interrelated challenges: how to adequately analyze, interpret, store, reanalyze and apply an unprecedented amount of genomic data (with uncertain clinical utility) to patient care? In addition, genomic data has the potential to become integral for improving the medical care of an individual and their family, years after a genome is sequenced. Current informed consent protocols do not adequately address the unique challenges and complexities inherent to the process of WGS/WES. This dissertation constructs a novel informed consent process for individuals considering WGS/WES, capable of fulfilling both legal and ethical requirements of medical consent while addressing the intricacies of WGS/WES, ultimately resulting in a more effective consenting experience. To better understand components of an effective consenting experience, the first part of this dissertation traces the historical origin of the informed consent process to identify the motivations, rationales and institutional commitments that sustain our current consenting protocols for genetic testing. After understanding the underlying commitments that shape our current informed consent protocols, I discuss the effectiveness of the informed consent process from an ethical and legal standpoint. I illustrate how WGS/WES introduces new complexities to the informed consent process and assess whether informed consent protocols proposed for WGS/WES address these complexities. The last section of this dissertation describes a novel informed consent process for WGS/WES, constructed from the original ethical intent of informed consent, analysis of existing informed consent protocols, and my own observations as a genetic counselor for what constitutes an effective consenting experience.
ContributorsHunt, Katherine (Author) / Hurlbut, J. Benjamin (Thesis advisor) / Robert, Jason S. (Thesis advisor) / Maienschein, Jane (Committee member) / Northfelt, Donald W. (Committee member) / Marchant, Gary (Committee member) / Ellison, Karin (Committee member) / Arizona State University (Publisher)
Created2013
152351-Thumbnail Image.png
Description
Lung Cancer Alliance, a nonprofit organization, released the "No One Deserves to Die" advertising campaign in June 2012. The campaign visuals presented a clean, simple message to the public: the stigma associated with lung cancer drives marginalization of lung cancer patients. Lung Cancer Alliance (LCA) asserts that negative public attitude

Lung Cancer Alliance, a nonprofit organization, released the "No One Deserves to Die" advertising campaign in June 2012. The campaign visuals presented a clean, simple message to the public: the stigma associated with lung cancer drives marginalization of lung cancer patients. Lung Cancer Alliance (LCA) asserts that negative public attitude toward lung cancer stems from unacknowledged moral judgments that generate 'stigma.' The campaign materials are meant to expose and challenge these common public category-making processes that occur when subconsciously evaluating lung cancer patients. These processes involve comparison, perception of difference, and exclusion. The campaign implies that society sees suffering of lung cancer patients as indicative of moral failure, thus, not warranting assistance from society, which leads to marginalization of the diseased. Attributing to society a morally laden view of the disease, the campaign extends this view to its logical end and makes it explicit: lung cancer patients no longer deserve to live because they themselves caused the disease (by smoking). This judgment and resulting marginalization is, according to LCA, evident in the ways lung cancer patients are marginalized relative to other diseases via minimal research funding, high- mortality rates and low awareness of the disease. Therefore, society commits an injustice against those with lung cancer. This research analyzes the relationship between disease, identity-making, and responsibilities within society as represented by this stigma framework. LCA asserts that society understands lung cancer in terms of stigma, and advocates that society's understanding of lung cancer should be shifted from a stigma framework toward a medical framework. Analysis of identity-making and responsibility encoded in both frameworks contributes to evaluation of the significance of reframing this disease. One aim of this thesis is to explore the relationship between these frameworks in medical sociology. The results show a complex interaction that suggest trading one frame for another will not destigmatize the lung cancer patient. Those interactions cause tangible harms, such as high mortality rates, and there are important implications for other communities that experience a stigmatized disease.
ContributorsCalvelage, Victoria (Author) / Hurlbut, J. Benjamin (Thesis advisor) / Maienschein, Jane (Committee member) / Ellison, Karin (Committee member) / Arizona State University (Publisher)
Created2013
152897-Thumbnail Image.png
Description
In-band full-duplex relays are envisioned as promising solution to increase the throughput of next generation wireless communications. Full-duplex relays, being able to transmit and receive at same carrier frequency, offers increased spectral efficiency compared to half-duplex relays that transmit and receive at different frequencies or times. The practical implementation of

In-band full-duplex relays are envisioned as promising solution to increase the throughput of next generation wireless communications. Full-duplex relays, being able to transmit and receive at same carrier frequency, offers increased spectral efficiency compared to half-duplex relays that transmit and receive at different frequencies or times. The practical implementation of full-duplex relays is limited by the strong self-interference caused by the coupling of relay's own transit signals to its desired received signals. Several techniques have been proposed in literature to mitigate the relay self-interference. In this thesis, the performance of in-band full-duplex multiple-input multiple-output (MIMO) relays is considered in the context of simultaneous communications and channel estimation. In particular, adaptive spatial transmit techniques is considered to protect the full-duplex radio's receive array. It is assumed that relay's transmit and receive antenna phase centers are physically distinct. This allows the radio to employ adaptive spatial transmit and receive processing to mitigate self-interference.

The performance of this protection is dependent upon numerous factors, including channel estimation accuracy, which is the focus of this thesis. In particular, the concentration is on estimating the self-interference channel. A novel approach of simultaneous signaling to estimate the self-interference channel in MIMO full-duplex relays is proposed. To achieve this simultaneous communications

and channel estimation, a full-rank pilot signal at a reduced relative power is transmitted simultaneously with a low rank communication waveform. The self-interference mitigation is investigated in the context of eigenvalue spread of spatial relay receive co-variance matrix. Performance is demonstrated by using simulations,

in which orthogonal-frequency division-multiplexing communications and pilot sequences are employed.
ContributorsSekhar, Kishore Kumar (Author) / Bliss, Daniel W (Thesis advisor) / Kitchen, Jennifer (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2014
152926-Thumbnail Image.png
Description
Teaching evolution has been shown to be a challenge for faculty, in both K-12 and postsecondary education. Many of these challenges stem from perceived conflicts not only between religion and evolution, but also faculty beliefs about religion, it's compatibility with evolutionary theory, and it's proper role in classroom curriculum. Studies

Teaching evolution has been shown to be a challenge for faculty, in both K-12 and postsecondary education. Many of these challenges stem from perceived conflicts not only between religion and evolution, but also faculty beliefs about religion, it's compatibility with evolutionary theory, and it's proper role in classroom curriculum. Studies suggest that if educators engage with students' religious beliefs and identity, this may help students have positive attitudes towards evolution. The aim of this study was to reveal attitudes and beliefs professors have about addressing religion and providing religious scientist role models to students when teaching evolution. 15 semi-structured interviews of tenured biology professors were conducted at a large Midwestern universiy regarding their beliefs, experiences, and strategies teaching evolution and particularly, their willingness to address religion in a class section on evolution. Following a qualitative analysis of transcripts, professors did not agree on whether or not it is their job to help students accept evolution (although the majority said it is not), nor did they agree on a definition of "acceptance of evolution". Professors are willing to engage in students' religious beliefs, if this would help their students accept evolution. Finally, professors perceived many challenges to engaging students' religious beliefs in a science classroom such as the appropriateness of the material for a science class, large class sizes, and time constraints. Given the results of this study, the author concludes that instructors must come to a consensus about their goals as biology educators as well as what "acceptance of evolution" means, before they can realistically apply the engagement of student's religious beliefs and identity as an educational strategy.
ContributorsBarnes, Maryann Elizabeth (Author) / Brownell, Sara E (Thesis advisor) / Brem, Sarah K. (Thesis advisor) / Lynch, John M. (Committee member) / Ellison, Karin (Committee member) / Arizona State University (Publisher)
Created2014