Browsing by Author "Scharf, Louis L., committee member"

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Open Access
Channel coding for network communication: an information theoretic perspective
(Colorado State University. Libraries, 2011) Wang, Zheng, author; Luo, J. Rockey, advisor; Scharf, Louis L., committee member; Chong, Edwin K. P., committee member; Betten, Anton, committee member
Channel coding helps a communication system to combat noise and interference by adding "redundancy" to the source message. Theoretical fundamentals of channel coding in point-to-point systems have been intensively studied in the research area of information theory, which was proposed by Claude Shannon in his celebrated work in 1948. A set of landmark results have been developed to characterize the performance limitations in terms of the rate and the reliability tradeoff bounds. However, unlike its success in point-to-point systems, information theory has not yielded as rich results in network communication, which has been a key research focus over the past two decades. Due to the limitations posed by some of the key assumptions in classical information theory, network information theory is far from being mature and complete. For example, the classical information theoretic model assumes that communication parameters such as the information rate should be jointly determined by all transmitters and receivers. Communication should be carried out continuously over a long time such that the overhead of communication coordination becomes negligible. The communication channel should be stationary in order for the coding scheme to transform the channel noise randomness into deterministic statistics. These assumptions are valid in a point-to-point system, but they do not permit an extensive application of channel coding in network systems because they have essentially ignored the dynamic nature of network communication. Network systems deal with bursty message transmissions between highly dynamic users. For various reasons, joint determination of key communication parameters before message transmission is often infeasible or expensive. Communication channels can often be non-stationary due to the dynamic communication interference generated by the network users. The objective of this work is to extend information theory toward network communication scenarios. We develop new channel coding results, in terms of the communication rate and error performance tradeoff, for several non-classical communication models, in which key assumptions made in classical channel coding are dropped or revised.
Open Access
Extraction, characterization and modeling of network data features - a compressive sensing and robust PCA based approach
(Colorado State University. Libraries, 2015) Bandara, Vidarshana W., author; Jayasumana, Anura P., advisor; Pezeshki, Ali, advisor; Scharf, Louis L., committee member; Ray, Indrajit, committee member; Luo, J. Rockey, committee member
To view the abstract, please see the full text of the document.
Open Access
Perfect tracking for non-minimum phase systems with applications to biofuels from microalgae
(Colorado State University. Libraries, 2010) Buehner, Michael R., author; Young, Peter M., advisor; Chong, Edwin Kah Pin, committee member; Scharf, Louis L., committee member; Anderson, Charles W., committee member
In a causal setting, a closed-loop control system receives reference inputs (with no a priori knowledge) that it must track. For this setting, controllers are designed that provide both stability and performance (e.g., to meet tracking and disturbance rejection requirements). Often, feedback controllers are designed to satisfy weighted optimization criteria (e.g., weighted tracking error) that are later validated using test signals such as step responses and frequency sweeps. Feedforward controllers may be used to improve the response to measurable external disturbances (e.g., reference inputs). In this way, they can improve the closed-loop response; however, these approaches do not directly specify the closed-loop response. Two controller architectures are developed that allow for directly designing the nominal closed-loop response of non-minimum phase systems. These architectures classify both the signals that may be perfectly tracked by a non-minimum phase plant and the control signals that provide this perfect tracking. For these architectures, perfect tracking means that the feedback error is zero (for all time) in the nominal case (i.e., the plant model is exact) when there are no external disturbances. For the controllers presented here, parts of the feedforward controllers are based on the plant model, while a separate piece is designed to provide the desired level of performance. One of the potential limitations to these designs is that the actual performance will depend upon the quality of the model used. Robustness tools are developed that may be used to determine the expected performance for a given level of model uncertainty. These robustness tools may also be used to design the piece of the feedforward controller that provides performance. There is a tradeoff between model uncertainty and achievable performance. In general, more model uncertainty will result in less achievable performance. Another way to approach the issue of performance is to consider that a good model must either be known a priori or learned via adaptation. In the cases where a good model is difficult to determine a priori, adaptation may be used to improve the models in the feedforward controllers, which will, in turn, improve the performance of the overall control system. We show how adaptive feedforward architectures can improve performance for systems where the model is of limited accuracy. An example application of growing microalgae for biofuel production is presented. Microalgae have the potential to produce enough biofuels to meet the current US fuel demands; however, progress has been limited (in some part) due to a lack of appropriate models and controllers. In the work presented here, models are developed that may be used to monitor the productivity of microalgae inside a photobioreactor and to develop control algorithms. We use experimental data from a functional prototype photobioreactor to validate these models and to demonstrate the advantages of the advanced controller architectures developed here.
Open Access
Saddlepoint approximation to functional equations in queueing theory and insurance mathematics
(Colorado State University. Libraries, 2010) Chung, Sunghoon, author; Butler, Ronald W., advisor; Scharf, Louis L., committee member; Chapman, Phillip L., committee member; Hoeting, Jennifer A. (Jennifer Ann), 1966-, committee member
We study the application of saddlepoint approximations to statistical inference when the moment generating function (MGF) of the distribution of interest is an explicit or an implicit function of the MGF of another random variable which is assumed to be observed. In other words, let W (s) be the MGF of the random variable W of interest. We study the case when W (s) = h{G (s) ; λ}, where G (s) is an MGF of G for which a random sample can be obtained, and h is a smooth function. If Ĝ (s) estimates G (s), then Ŵ (s) = h{Ĝ (s) ; λ̂} estimates W (s). Generally, it can be shown that Ŵ (s) converges to W (s) by the strong law of large numbers, which implies that F̂ (t), the cumulative distribution function (CDF) corresponding to Ŵ (s), converges to F (t), the CDF of W, almost surely. If we set Ŵ* (s) = h{Ĝ* (s) ; λ̂}, where Ĝ* (s) and λ̂* are the empirical MGF and the estimator of λ from bootstrapping, the corresponding CDF F̂* (t) can be used to construct the confidence band of F(t). In this dissertation, we show that the saddlepoint inversion of Ŵ (s) is not only fast, reliable, stable, and accurate enough for a general statistical inference, but also easy to use without deep knowledge of the probability theory regarding the stochastic process of interest. For the first part, we consider nonparametric estimation of the density and the CDF of the stationary waiting times W and Wq of an M/G/1 queue. These estimates are computed using saddlepoint inversion of Ŵ (s) determined from the Pollaczek-Khinchin formula. Our saddlepoint estimation is compared with estimators based on other approximations, including the Cramér-Lundberg approximation. For the second part, we consider the saddlepoint approximation for the busy period distribution FB (t) in a M/G/1 queue. The busy period B is the first passage time for the queueing system to pass from an initial arrival (1 in the system) to 0 in the system. If B (s) is the MGF of B, then B (s) is an implicitly defined function of G (s) and λ, the inter-arrival rate, through the well-known Kendall-Takács functional equation. As in the first part, we show that the saddlepoint approximation can be used to obtain F̂B (t), the CDF corresponding to B̂(s) and simulation results show that confidence bands of FB (t) based on bootstrapping perform well.
Open Access
Sensing, communications and monitoring for the smart grid
(Colorado State University. Libraries, 2012) Duan, Dongliang, author; Yang, Liuqing, advisor; Scharf, Louis L., committee member; Luo, Jie, committee member; Song, Rui, committee member
With the increasing concern for environmental factors, reliability, and quality of service, power grids in many countries are undergoing revolution towards a more distributed and flexible "smart grid." In the development of the envisioned smart grid, situational awareness takes a fundamental role for a number of crucial advanced operations, such as power flow scheduling, dynamic pricing, energy management, wide area control, wide area protection etc. To fulfill the mission of situational awareness across various entities in the grid, more advanced sensing, communications and monitoring techniques need to be introduced to the existing power grid. In this research, we will first address the issue of battery power efficiency (BPE) in a wireless sensor network (WSN) which is essential for the sensing system lifetime. We show that the BPE can be improved either by selecting a more battery-power-efficient modulation format or by developing a cooperative communications scheme. Then, to transmit the sensed data over the scarse wireless bandwidth, we adopt cognitive radio as a possible solution. To enable the cognitive radio communication, we aim at improving both the reliability and efficiency of the overall system via cooperative spectrum sensing. With these fundamental communication capabilities available for the sensed data, we then investigate wide area power grid monitoring based on synchronized measurements from newly developed devices such as phasor measurement units (PMUs), mode meters and so on. In addition, an optimal fusion technique is studied as a good foundation for detection in wireless sensor networks, with application to event detection in the power grid.
Open Access
Target tracking with distributed sensing: information-theoretic bounds and closed-loop scheduling for urban terrain
(Colorado State University. Libraries, 2010) de Rezende Barbosa, Patricia, author; Chong, Edwin K. P., advisor; Scharf, Louis L., committee member; Luo, J. Rockey, committee member; Lee, Chihoon, committee member
We address both theoretical and practical aspects of target tracking in a distributed sensing environment. First, we consider the problem of tracking a target that moves according to a Markov chain in a sensor network. We provide necessary and sufficient conditions on the number of (queries per time step to track a target in three different scenarios: (1) the tracker is required to know the exact location of the target at each time step; (2) the tracker may lose track of the target at a given time step, but it is able to “catch-up”, regaining up-to-date information about the target’s track; and (3) tracking information is only known by the tracker after a delay of d time steps. We then address the problem of target tracking in urban terrain. Specifically, we investigate' the integration of detection, signal processing, tracking, and scheduling, by simultaneously exploiting three diversity modes: (1) spatial diversity through the use of coordinated multistatic radars; (2) waveform diversity by adaptively scheduling the transmitted waveform; and (3) motion model diversity by using a bank of parallel filters matched to different motion models. A closed-loop active sensing system is presented, and Monte Carlo simulations demonstrate its effectiveness in urban terrain. Finally, we propose a scheduling scheme that adaptively selects the sequence of transmitters and waveforms that maximizes the overall tracking accuracy, while maintaining the sensing system’s covertness in a hostile environment. We formulate this problem as a POMDP and use two distinct schedulers: (1) a myopic scheduler that updates waveforms at every radar scan; and (2) a non-myopic scheduler that activates a new set of transmitters if the overall tracking accuracy falls below a threshold or if a detection risk is exceeded. By simultaneously exploiting myopic and non-myopic scheduling schemes, with benefit from trading off short-term for long-term performance, while maintaining low computational costs. Monte Carlo simulations are used to evaluate the proposed scheduling scheme in a multitarget tracking setting.