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- Creators: Bakkaloglu, Bertan
Description
Distributed estimation uses many inexpensive sensors to compose an accurate estimate of a given parameter. It is frequently implemented using wireless sensor networks. There have been several studies on optimizing power allocation in wireless sensor networks used for distributed estimation, the vast majority of which assume linear radio-frequency amplifiers. Linear amplifiers are inherently inefficient, so in this dissertation nonlinear amplifiers are examined to gain efficiency while operating distributed sensor networks. This research presents a method to boost efficiency by operating the amplifiers in the nonlinear region of operation. Operating amplifiers nonlinearly presents new challenges. First, nonlinear amplifier characteristics change across manufacturing process variation, temperature, operating voltage, and aging. Secondly, the equations conventionally used for estimators and performance expectations in linear amplify-and-forward systems fail. To compensate for the first challenge, predistortion is utilized not to linearize amplifiers but rather to force them to fit a common nonlinear limiting amplifier model close to the inherent amplifier performance. This minimizes the power impact and the training requirements for predistortion. Second, new estimators are required that account for transmitter nonlinearity. This research derives analytically and confirms via simulation new estimators and performance expectation equations for use in nonlinear distributed estimation. An additional complication when operating nonlinear amplifiers in a wireless environment is the influence of varied and potentially unknown channel gains. The impact of these varied gains and both measurement and channel noise sources on estimation performance are analyzed in this paper. Techniques for minimizing the estimate variance are developed. It is shown that optimizing transmitter power allocation to minimize estimate variance for the most-compressed parameter measurement is equivalent to the problem for linear sensors. Finally, a method for operating distributed estimation in a multipath environment is presented that is capable of developing robust estimates for a wide range of Rician K-factors. This dissertation demonstrates that implementing distributed estimation using nonlinear sensors can boost system efficiency and is compatible with existing techniques from the literature for boosting efficiency at the system level via sensor power allocation. Nonlinear transmitters work best when channel gains are known and channel noise and receiver noise levels are low.
ContributorsSantucci, Robert (Author) / Spanias, Andreas (Thesis advisor) / Tepedelenlioðlu, Cihan (Committee member) / Bakkaloglu, Bertan (Committee member) / Tsakalis, Kostas (Committee member) / Arizona State University (Publisher)
Created2013
Description
Many different levels of government, organizations, and programs actively shape the future of energy in Arizona, a state that lacks a comprehensive energy plan. Disparate actions by multiple actors may slow the energy policy process rather than expedite it. The absence of a state energy policy or plan raises questions about how multiple actors and ideas engage with state energy policy development and whether the absence of a comprehensive state plan can be understood. Improving how policy development is conceptualized and giving more focused attention to the mechanisms by which interested parties become involved in shaping Arizona energy policy. To explore these questions, I examine the future energy efficiency. Initially, public engagement mechanisms were examined for their role in policy creation from a theoretical perspective. Next a prominent public engagement forum that was dedicated to the topic of the Arizona's energy future was examined, mapping its process and conclusions onto a policy process model. The first part of this thesis involves an experimental expert consultation panel which was convened to amplify and refine the results of a public forum. The second part utilizes an online follow up survey to complete unfinished ideas from the focus group. The experiment flowed from a hypothesis that formal expert discussion on energy efficiency policies, guided by the recommendations put forth by the public engagement forum on energy in Arizona, would result in an increase in relevance while providing a forum for interdisciplinary collaboration that is atypical in today's energy discussions. This experiment was designed and evaluated utilizing a public engagement framework that incorporated theoretical and empirical elements. Specifically, I adapted elements of three methods of public and expert engagement used in policy development to create a consultation process that was contextualized to energy efficiency stakeholders in Arizona and their unique constraints. The goal of the consultation process was to refine preferences about policy options by expert stakeholders into actionable goals that could achieve advancement on policy implementation. As a corollary goal, the research set out to define implementation barriers, refine policy ideas, and operationalize Arizona-centric goals for the future of energy efficiency.
ContributorsBryck, Drew (Author) / Graffy, Elisabeth A. (Thesis advisor) / Dalrymple, Michael (Committee member) / Miller, Clark (Committee member) / Arizona State University (Publisher)
Created2013