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- All Subjects: Stochastic orders
- All Subjects: power grid
- Genre: Doctoral Dissertation
- Creators: Kosut, Oliver
- Member of: Theses and Dissertations
- Resource Type: Text
Description
This dissertation introduces stochastic ordering of instantaneous channel powers of fading channels as a general method to compare the performance of a communication system over two different channels, even when a closed-form expression for the metric may not be available. Such a comparison is with respect to a variety of performance metrics such as error rates, outage probability and ergodic capacity, which share common mathematical properties such as monotonicity, convexity or complete monotonicity. Complete monotonicity of a metric, such as the symbol error rate, in conjunction with the stochastic Laplace transform order between two fading channels implies the ordering of the two channels with respect to the metric. While it has been established previously that certain modulation schemes have convex symbol error rates, there is no study of the complete monotonicity of the same, which helps in establishing stronger channel ordering results. Toward this goal, the current research proves for the first time, that all 1-dimensional and 2-dimensional modulations have completely monotone symbol error rates. Furthermore, it is shown that the frequently used parametric fading distributions for modeling line of sight exhibit a monotonicity in the line of sight parameter with respect to the Laplace transform order. While the Laplace transform order can also be used to order fading distributions based on the ergodic capacity, there exist several distributions which are not Laplace transform ordered, although they have ordered ergodic capacities. To address this gap, a new stochastic order called the ergodic capacity order has been proposed herein, which can be used to compare channels based on the ergodic capacity. Using stochastic orders, average performance of systems involving multiple random variables are compared over two different channels. These systems include diversity combining schemes, relay networks, and signal detection over fading channels with non-Gaussian additive noise. This research also addresses the problem of unifying fading distributions. This unification is based on infinite divisibility, which subsumes almost all known fading distributions, and provides simplified expressions for performance metrics, in addition to enabling stochastic ordering.
ContributorsRajan, Adithya (Author) / Tepedelenlioğlu, Cihan (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Bliss, Daniel (Committee member) / Kosut, Oliver (Committee member) / Arizona State University (Publisher)
Created2014
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
Our daily life is becoming more and more reliant on services provided by the infrastructures
power, gas , communication networks. Ensuring the security of these
infrastructures is of utmost importance. This task becomes ever more challenging as
the inter-dependence among these infrastructures grows and a security breach in one
infrastructure can spill over to the others. The implication is that the security practices/
analysis recommended for these infrastructures should be done in coordination.
This thesis, focusing on the power grid, explores strategies to secure the system that
look into the coupling of the power grid to the cyber infrastructure, used to manage
and control it, and to the gas grid, that supplies an increasing amount of reserves to
overcome contingencies.
The first part (Part I) of the thesis, including chapters 2 through 4, focuses on
the coupling of the power and the cyber infrastructure that is used for its control and
operations. The goal is to detect malicious attacks gaining information about the
operation of the power grid to later attack the system. In chapter 2, we propose a
hierarchical architecture that correlates the analysis of high resolution Micro-Phasor
Measurement Unit (microPMU) data and traffic analysis on the Supervisory Control
and Data Acquisition (SCADA) packets, to infer the security status of the grid and
detect the presence of possible intruders. An essential part of this architecture is
tied to the analysis on the microPMU data. In chapter 3 we establish a set of anomaly
detection rules on microPMU data that
flag "abnormal behavior". A placement strategy
of microPMU sensors is also proposed to maximize the sensitivity in detecting anomalies.
In chapter 4, we focus on developing rules that can localize the source of an events
using microPMU to further check whether a cyber attack is causing the anomaly, by
correlating SCADA traffic with the microPMU data analysis results. The thread that
unies the data analysis in this chapter is the fact that decision are made without fully estimating the state of the system; on the contrary, decisions are made using
a set of physical measurements that falls short by orders of magnitude to meet the
needs for observability. More specifically, in the first part of this chapter (sections 4.1-
4.2), using microPMU data in the substation, methodologies for online identification of
the source Thevenin parameters are presented. This methodology is used to identify
reconnaissance activity on the normally-open switches in the substation, initiated
by attackers to gauge its controllability over the cyber network. The applications
of this methodology in monitoring the voltage stability of the grid is also discussed.
In the second part of this chapter (sections 4.3-4.5), we investigate the localization
of faults. Since the number of PMU sensors available to carry out the inference
is insufficient to ensure observability, the problem can be viewed as that of under-sampling
a "graph signal"; the analysis leads to a PMU placement strategy that can
achieve the highest resolution in localizing the fault, for a given number of sensors.
In both cases, the results of the analysis are leveraged in the detection of cyber-physical
attacks, where microPMU data and relevant SCADA network traffic information
are compared to determine if a network breach has affected the integrity of the system
information and/or operations.
In second part of this thesis (Part II), the security analysis considers the adequacy
and reliability of schedules for the gas and power network. The motivation for
scheduling jointly supply in gas and power networks is motivated by the increasing
reliance of power grids on natural gas generators (and, indirectly, on gas pipelines)
as providing critical reserves. Chapter 5 focuses on unveiling the challenges and
providing solution to this problem.
power, gas , communication networks. Ensuring the security of these
infrastructures is of utmost importance. This task becomes ever more challenging as
the inter-dependence among these infrastructures grows and a security breach in one
infrastructure can spill over to the others. The implication is that the security practices/
analysis recommended for these infrastructures should be done in coordination.
This thesis, focusing on the power grid, explores strategies to secure the system that
look into the coupling of the power grid to the cyber infrastructure, used to manage
and control it, and to the gas grid, that supplies an increasing amount of reserves to
overcome contingencies.
The first part (Part I) of the thesis, including chapters 2 through 4, focuses on
the coupling of the power and the cyber infrastructure that is used for its control and
operations. The goal is to detect malicious attacks gaining information about the
operation of the power grid to later attack the system. In chapter 2, we propose a
hierarchical architecture that correlates the analysis of high resolution Micro-Phasor
Measurement Unit (microPMU) data and traffic analysis on the Supervisory Control
and Data Acquisition (SCADA) packets, to infer the security status of the grid and
detect the presence of possible intruders. An essential part of this architecture is
tied to the analysis on the microPMU data. In chapter 3 we establish a set of anomaly
detection rules on microPMU data that
flag "abnormal behavior". A placement strategy
of microPMU sensors is also proposed to maximize the sensitivity in detecting anomalies.
In chapter 4, we focus on developing rules that can localize the source of an events
using microPMU to further check whether a cyber attack is causing the anomaly, by
correlating SCADA traffic with the microPMU data analysis results. The thread that
unies the data analysis in this chapter is the fact that decision are made without fully estimating the state of the system; on the contrary, decisions are made using
a set of physical measurements that falls short by orders of magnitude to meet the
needs for observability. More specifically, in the first part of this chapter (sections 4.1-
4.2), using microPMU data in the substation, methodologies for online identification of
the source Thevenin parameters are presented. This methodology is used to identify
reconnaissance activity on the normally-open switches in the substation, initiated
by attackers to gauge its controllability over the cyber network. The applications
of this methodology in monitoring the voltage stability of the grid is also discussed.
In the second part of this chapter (sections 4.3-4.5), we investigate the localization
of faults. Since the number of PMU sensors available to carry out the inference
is insufficient to ensure observability, the problem can be viewed as that of under-sampling
a "graph signal"; the analysis leads to a PMU placement strategy that can
achieve the highest resolution in localizing the fault, for a given number of sensors.
In both cases, the results of the analysis are leveraged in the detection of cyber-physical
attacks, where microPMU data and relevant SCADA network traffic information
are compared to determine if a network breach has affected the integrity of the system
information and/or operations.
In second part of this thesis (Part II), the security analysis considers the adequacy
and reliability of schedules for the gas and power network. The motivation for
scheduling jointly supply in gas and power networks is motivated by the increasing
reliance of power grids on natural gas generators (and, indirectly, on gas pipelines)
as providing critical reserves. Chapter 5 focuses on unveiling the challenges and
providing solution to this problem.
ContributorsJamei, Mahdi (Author) / Scaglioe, Anna (Thesis advisor) / Ayyanar, Raja (Committee member) / Hedman, Kory W (Committee member) / Kosut, Oliver (Committee member) / Arizona State University (Publisher)
Created2018