Reconfigurable Sampling for Enhanced Energy Efficiency in Power-Constrained Wireless Systems

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Publicado en:ProQuest Dissertations and Theses (2011)
Autor principal: Kurp, Timothy Daniel
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ProQuest Dissertations & Theses
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100 1 |a Kurp, Timothy Daniel 
245 1 |a Reconfigurable Sampling for Enhanced Energy Efficiency in Power-Constrained Wireless Systems 
260 |b ProQuest Dissertations & Theses  |c 2011 
513 |a Dissertation/Thesis 
520 3 |a Advancement in microelectronics and wireless communications has nurtured the development of low power and low cost wireless systems such as sensor networks. Each node is typically driven by a battery, which has a limited energy capacity that directly constrains node, and network lifetime. This presents a bottleneck for the widespread exploitation of wireless sensing technology. Therefore, improving the energy efficiency of wireless sensing devices is of critical importance and has attracted the attention of the research community. In this work, a data-driven method has been proposed and systematically investigated. Specifically, this technique reconfigures, in real time, the rate of data sampling based on the information content of the data acquired in the preceding step. Through this technique, significant reduction in energy usage and data load can be achieved, as is analytically and experimentally demonstrated in this work. The problem of reconfigurable data sampling as opposed to the traditional fixed-rate sampling is analytically and numerically evaluated. An algorithm that efficiently tracks the signal spectral properties has been developed, utilizing a novel filtering scheme based on the wavelet packet transform (WPT). Key elements of the algorithm include selective computation of WPT coefficients for sampling rate selection. Additionally, a signal reconstruction procedure has been derived for the case of non-uniform sampling, which allows the signal to be retrieved from the adaptively acquired samples. A post-analysis has also been formulated to quantify error in sampling rate adjustment. Simulation and experimental studies indicate significant data reduction leading to decreased energy consumption, while maintaining signal fidelity. 
653 |a Sparsity 
653 |a Microelectromechanical systems 
653 |a Fixed rates 
653 |a Consumers 
653 |a Wavelet transforms 
653 |a Fourier transforms 
653 |a Sampling techniques 
653 |a Communication 
653 |a Bandwidths 
653 |a Power 
653 |a Decision making 
653 |a Signal processing 
653 |a Decomposition 
653 |a Energy efficiency 
653 |a Transmitters 
653 |a Digital signal processors 
653 |a Cost control 
653 |a Energy consumption 
653 |a Engineering research 
653 |a Electrical engineering 
653 |a Mathematics 
653 |a Mechanical engineering 
773 0 |t ProQuest Dissertations and Theses  |g (2011) 
786 0 |d ProQuest  |t ProQuest Dissertations & Theses Global 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3073205895/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3073205895/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch