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Distributed Inference over Multiple-Access Channels with Wireless Sensor Networks


Abstract Distributed inference has applications in fields as varied as source localization, evaluation of network quality, and remote monitoring of wildlife habitats. In this dissertation, distributed inference algorithms over multiple-access channels are considered. The performance of these algorithms and the effects of wireless communication channels on the performance are studied. In a first class of problems, distributed inference over fading Gaussian multiple-access channels with amplify-and-forward is considered. Sensors observe a phenomenon and transmit their observations using the amplify-and-forward scheme to a fusion center (FC). Distributed estimation is considered with a single antenna at the FC, where the performance is evaluated using ... (more)
Created Date 2010
Contributor Banavar, Mahesh Krishna (Author) / Tepedelenlioglu, Cihan (Advisor) / Spanias, Andreas (Advisor) / Papandreou-Suppappola, Antonia (Committee member) / Duman, Tolga (Committee member) / Zhang, Junshan (Committee member) / Arizona State University (Publisher)
Subject Electrical Engineering / Asymptotic Variance / Channel Feedback / Distributed Inference / Fading Channels / Multiple Antennas / Wireless Sensor Networks
Type Doctoral Dissertation
Extent 132 pages
Language English
Copyright
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Note Ph.D. Electrical Engineering 2010
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS


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Description Dissertation/Thesis