ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- Creators: Spanias, Andreas
Due to deep neural networks' need of large training sets for accurate performance, this thesis outlines the design and implementation of an autonomous channel measurement system to analyze the performance of the proposed deep learning based channel mapping concept. This system obtains channel magnitude measurements from eight antennas autonomously using a mobile robot carrying a transmitter which receives wireless commands from the central computer connected to the static receiver system. The developed autonomous channel measurement system is capable of obtaining accurate and repeatable channel magnitude measurements. It is shown that the proposed deep learning based channel mapping system accurately predicts channel information containing few multi-path effects.