Matching Items (32)
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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

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
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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

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
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Description
The problem of cooperative radar and communications signaling is investigated. Each system typically considers the other system a source of interference. Consequently, the tradition is to have them operate in orthogonal frequency bands. By considering the radar and communications operations to be a single joint system, performance bounds on a

The problem of cooperative radar and communications signaling is investigated. Each system typically considers the other system a source of interference. Consequently, the tradition is to have them operate in orthogonal frequency bands. By considering the radar and communications operations to be a single joint system, performance bounds on a receiver that observes communications and radar return in the same frequency allocation are derived. Bounds in performance of the joint system is measured in terms of data information rate for communications and radar estimation information rate for the radar. Inner bounds on performance are constructed.
ContributorsChiriyath, Alex (Author) / Bliss, Daniel W (Thesis advisor) / Kosut, Oliver (Committee member) / Berisha, Visar (Committee member) / Arizona State University (Publisher)
Created2014
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Description
The electric power system is one of the largest, most complicated, and most important cyber-physical systems in the world. The link between the cyber and physical level is the Supervisory Control and Data Acquisition (SCADA) systems and Energy Management Systems (EMS). Their functions include monitoring the real-time system operation

The electric power system is one of the largest, most complicated, and most important cyber-physical systems in the world. The link between the cyber and physical level is the Supervisory Control and Data Acquisition (SCADA) systems and Energy Management Systems (EMS). Their functions include monitoring the real-time system operation through state estimation (SE), controlling the system to operate reliably, and optimizing the system operation efficiency. The SCADA acquires the noisy measurements, such as voltage angle and magnitude, line power flows, and line current magnitude, from the remote terminal units (RTUs). These raw data are firstly sent to the SE, which filters all the noisy data and derives the best estimate of the system state. Then the estimated states are used for other EMS functions, such as contingency analysis, optimal power flow, etc.

In the existing state estimation process, there is no defense mechanism for any malicious attacks. Once the communication channel between the SCADA and RTUs is hijacked by the attacker, the attacker can perform a man-in-middle attack and send data of its choice. The only step that can possibly detect the attack during the state estimation process is the bad data detector. Unfortunately, even the bad data detector is unable to detect a certain type of attack, known as the false data injection (FDI) attacks.

Diagnosing the physical consequences of such attacks, therefore, is very important to understand system stability. In this thesis, theoretical general attack models for AC and DC attacks are given and an optimization problem for the worst-case overload attack is formulated. Furthermore, physical consequences of FDI attacks, based on both DC and AC model, are addressed. Various scenarios with different attack targets and system configurations are simulated. The details of the research, results obtained and conclusions drawn are presented in this document.
ContributorsLiang, Jingwen (Author) / Sankar, Lalitha (Thesis advisor) / Kosut, Oliver (Thesis advisor) / Hedman, Kory (Committee member) / Arizona State University (Publisher)
Created2015
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Description
The large distributed electric power system is a hierarchical network involving the

transportation of power from the sources of power generation via an intermediate

densely connected transmission network to a large distribution network of end-users

at the lowest level of the hierarchy. At each level of the hierarchy (generation/ trans-

mission/ distribution), the system

The large distributed electric power system is a hierarchical network involving the

transportation of power from the sources of power generation via an intermediate

densely connected transmission network to a large distribution network of end-users

at the lowest level of the hierarchy. At each level of the hierarchy (generation/ trans-

mission/ distribution), the system is managed and monitored with a combination of

(a) supervisory control and data acquisition (SCADA); and (b) energy management

systems (EMSs) that process the collected data and make control and actuation de-

cisions using the collected data. However, at all levels of the hierarchy, both SCADA

and EMSs are vulnerable to cyber attacks. Furthermore, given the criticality of the

electric power infrastructure, cyber attacks can have severe economic and social con-

sequences.

This thesis focuses on cyber attacks on SCADA and EMS at the transmission

level of the electric power system. The goal is to study the consequences of three

classes of cyber attacks that can change topology data. These classes include: (i)

unobservable state-preserving cyber attacks that only change the topology data; (ii)

unobservable state-and-topology cyber-physical attacks that change both states and

topology data to enable a coordinated physical and cyber attack; and (iii) topology-

targeted man-in-the-middle (MitM) communication attacks that alter topology data

shared during inter-EMS communication. Specically, attack class (i) and (ii) focus on

the unobservable attacks on single regional EMS while class (iii) focuses on the MitM

attacks on communication links between regional EMSs. For each class of attacks,

the theoretical attack model and the implementation of attacks are provided, and the

worst-case attack and its consequences are exhaustively studied. In particularly, for

class (ii), a two-stage optimization problem is introduced to study worst-case attacks

that can cause a physical line over

ow that is unobservable in the cyber layer. The long-term implication and the system anomalies are demonstrated via simulation.

For attack classes (i) and (ii), both mathematical and experimental analyses sug-

gest that these unobservable attacks can be limited or even detected with resiliency

mechanisms including load monitoring, anomalous re-dispatches checking, and his-

torical data comparison. For attack class (iii), countermeasures including anomalous

tie-line interchange verication, anomalous re-dispatch alarms, and external contin-

gency lists sharing are needed to thwart such attacks.
ContributorsZhang, Jiazi (Author) / Sankar, Lalitha (Thesis advisor) / Hedman, Kory (Committee member) / Kosut, Oliver (Committee member) / Arizona State University (Publisher)
Created2015
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Description
The electric power system is monitored via an extensive network of sensors in tandem with data processing algorithms, i.e., an intelligent cyber layer, that enables continual observation and control of the physical system to ensure reliable operations. This data collection and processing system is vulnerable to cyber-attacks that impact the

The electric power system is monitored via an extensive network of sensors in tandem with data processing algorithms, i.e., an intelligent cyber layer, that enables continual observation and control of the physical system to ensure reliable operations. This data collection and processing system is vulnerable to cyber-attacks that impact the system operation status and lead to serious physical consequences, including systematic problems and failures.

This dissertation studies the physical consequences of unobservable false data injection (FDI) attacks wherein the attacker maliciously changes supervisory control and data acquisition (SCADA) or phasor measurement unit (PMU) measurements, on the electric power system. In this context, the dissertation is divided into three parts, in which the first two parts focus on FDI attacks on SCADA and the last part focuses on FDI attacks on PMUs.

The first part studies the physical consequences of FDI attacks on SCADA measurements designed with limited system information. The attacker is assumed to have perfect knowledge inside a sub-network of the entire system. Two classes of attacks with different assumptions on the attacker's knowledge outside of the sub-network are introduced. In particular, for the second class of attacks, the attacker is assumed to have no information outside of the attack sub-network, but can perform multiple linear regression to learn the relationship between the external network and the attack sub-network with historical data. To determine the worst possible consequences of both classes of attacks, a bi-level optimization problem wherein the first level models the attacker's goal and the second level models the system response is introduced.

The second part of the dissertation concentrates on analyzing the vulnerability of systems to FDI attacks from the perspective of the system. To this end, an off-line vulnerability analysis framework is proposed to identify the subsets of the test system that are more prone to FDI attacks.

The third part studies the vulnerability of PMUs to FDI attacks. Two classes of more sophisticated FDI attacks that capture the temporal correlation of PMU data are introduced. Such attacks are designed with a convex optimization problem and can always bypass both the bad data detector and the low-rank decomposition (LD) detector.
ContributorsZhang, Jiazi (Author) / Sankar, Lalitha (Thesis advisor) / Kosut, Oliver (Committee member) / Hedman, Kory (Committee member) / Vittal, Vijay (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Spectral congestion is quickly becoming a problem for the telecommunications sector. In order to alleviate spectral congestion and achieve electromagnetic radio frequency (RF) convergence, communications and radar systems are increasingly encouraged to share bandwidth. In direct opposition to the traditional spectrum sharing approach between radar and communications systems of complete

Spectral congestion is quickly becoming a problem for the telecommunications sector. In order to alleviate spectral congestion and achieve electromagnetic radio frequency (RF) convergence, communications and radar systems are increasingly encouraged to share bandwidth. In direct opposition to the traditional spectrum sharing approach between radar and communications systems of complete isolation (temporal, spectral or spatial), both systems can be jointly co-designed from the ground up to maximize their joint performance for mutual benefit. In order to properly characterize and understand cooperative spectrum sharing between radar and communications systems, the fundamental limits on performance of a cooperative radar-communications system are investigated. To facilitate this investigation, performance metrics are chosen in this dissertation that allow radar and communications to be compared on the same scale. To that effect, information is chosen as the performance metric and an information theoretic radar performance metric compatible with the communications data rate, the radar estimation rate, is developed. The estimation rate measures the amount of information learned by illuminating a target. With the development of the estimation rate, standard multi-user communications performance bounds are extended with joint radar-communications users to produce bounds on the performance of a joint radar-communications system. System performance for variations of the standard spectrum sharing problem defined in this dissertation are investigated, and inner bounds on performance are extended to account for the effect of continuous radar waveform optimization, multiple radar targets, clutter, phase noise, and radar detection. A detailed interpretation of the estimation rate and a brief discussion on how to use these performance bounds to select an optimal operating point and achieve RF convergence are provided.
ContributorsChiriyath, Alex Rajan (Author) / Bliss, Daniel W (Thesis advisor) / Cochran, Douglas (Committee member) / Kosut, Oliver (Committee member) / Richmond, Christ D (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Fundamental limits of fixed-to-variable (F-V) and variable-to-fixed (V-F) length universal source coding at short blocklengths is characterized. For F-V length coding, the Type Size (TS) code has previously been shown to be optimal up to the third-order rate for universal compression of all memoryless sources over finite alphabets. The TS

Fundamental limits of fixed-to-variable (F-V) and variable-to-fixed (V-F) length universal source coding at short blocklengths is characterized. For F-V length coding, the Type Size (TS) code has previously been shown to be optimal up to the third-order rate for universal compression of all memoryless sources over finite alphabets. The TS code assigns sequences ordered based on their type class sizes to binary strings ordered lexicographically.

Universal F-V coding problem for the class of first-order stationary, irreducible and aperiodic Markov sources is first considered. Third-order coding rate of the TS code for the Markov class is derived. A converse on the third-order coding rate for the general class of F-V codes is presented which shows the optimality of the TS code for such Markov sources.

This type class approach is then generalized for compression of the parametric sources. A natural scheme is to define two sequences to be in the same type class if and only if they are equiprobable under any model in the parametric class. This natural approach, however, is shown to be suboptimal. A variation of the Type Size code is introduced, where type classes are defined based on neighborhoods of minimal sufficient statistics. Asymptotics of the overflow rate of this variation is derived and a converse result establishes its optimality up to the third-order term. These results are derived for parametric families of i.i.d. sources as well as Markov sources.

Finally, universal V-F length coding of the class of parametric sources is considered in the short blocklengths regime. The proposed dictionary which is used to parse the source output stream, consists of sequences in the boundaries of transition from low to high quantized type complexity, hence the name Type Complexity (TC) code. For large enough dictionary, the $\epsilon$-coding rate of the TC code is derived and a converse result is derived showing its optimality up to the third-order term.
ContributorsIri, Nematollah (Author) / Kosut, Oliver (Thesis advisor) / Bliss, Daniel (Committee member) / Sankar, Lalitha (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Energy management system (EMS) is at the heart of the operation and control of a modern electrical grid. Because of economic, safety, and security reasons, access to industrial grade EMS and real-world power system data is extremely limited. Therefore, the ability to simulate an EMS is invaluable in researching the

Energy management system (EMS) is at the heart of the operation and control of a modern electrical grid. Because of economic, safety, and security reasons, access to industrial grade EMS and real-world power system data is extremely limited. Therefore, the ability to simulate an EMS is invaluable in researching the EMS in normal and anomalous operating conditions.

I first lay the groundwork for a basic EMS loop simulation in modern power grids and review a class of cybersecurity threats called false data injection (FDI) attacks. Then I propose a software architecture as the basis of software simulation of the EMS loop and explain an actual software platform built using the proposed architecture. I also explain in detail the power analysis libraries used for building the platform with examples and illustrations from the implemented application. Finally, I will use the platform to simulate FDI attacks on two synthetic power system test cases and analyze and visualize the consequences using the capabilities built into the platform.
ContributorsKhodadadeh, Roozbeh (Author) / Sankar, Lalitha (Thesis advisor) / Xue, Guoliang (Thesis advisor) / Kosut, Oliver (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Both two-way relays (TWR) and full-duplex (FD) radios are spectrally efficient, and their integration shows great potential to further improve the spectral efficiency, which offers a solution to the fifth generation wireless systems. High quality channel state information (CSI) are the key components for the implementation and the performance of

Both two-way relays (TWR) and full-duplex (FD) radios are spectrally efficient, and their integration shows great potential to further improve the spectral efficiency, which offers a solution to the fifth generation wireless systems. High quality channel state information (CSI) are the key components for the implementation and the performance of the FD TWR system, making channel estimation in FD TWRs crucial.

The impact of channel estimation on spectral efficiency in half-duplex multiple-input-multiple-output (MIMO) TWR systems is investigated. The trade-off between training and data energy is proposed. In the case that two sources are symmetric in power and number of antennas, a closed-form for the optimal ratio of data energy to total energy is derived. It can be shown that the achievable rate is a monotonically increasing function of the data length. The asymmetric case is discussed as well.

Efficient and accurate training schemes for FD TWRs are essential for profiting from the inherent spectrally efficient structures of both FD and TWRs. A novel one-block training scheme with a maximum likelihood (ML) estimator is proposed to estimate the channels between the nodes and the residual self-interference (RSI) channel simultaneously. Baseline training schemes are also considered to compare with the one-block scheme. The Cramer-Rao bounds (CRBs) of the training schemes are derived and analyzed by using the asymptotic properties of Toeplitz matrices. The benefit of estimating the RSI channel is shown analytically in terms of Fisher information.

To obtain fundamental and analytic results of how the RSI affects the spectral efficiency, one-way FD relay systems are studied. Optimal training design and ML channel estimation are proposed to estimate the RSI channel. The CRBs are derived and analyzed in closed-form so that the optimal training sequence can be found via minimizing the CRB. Extensions of the training scheme to frequency-selective channels and multiple relays are also presented.

Simultaneously sensing and transmission in an FD cognitive radio system with MIMO is considered. The trade-off between the transmission rate and the detection accuracy is characterized by the sum-rate of the primary and the secondary users. Different beamforming and combining schemes are proposed and compared.
ContributorsLi, Xiaofeng (Author) / Tepedelenlioğlu, Cihan (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Bliss, Daniel W (Committee member) / Kosut, Oliver (Committee member) / Arizona State University (Publisher)
Created2018