This research solves current RF propagation modeling gaps by modifying a single-frequency electromagnetic propagation analysis technique for use on communication signals and propagation channels. This research extended the Methods of Ordered Multiple Interactions (MOMI) algorithm to communication signal propagation studies through the use of Fourier decomposition thereby allowing the analysis and prediction of communication signals propagating over rough surfaces.
Current methods of predicting and analyzing communication signal propagation rely on either using only a single frequency instead of a band of frequencies, stochastic techniques that model the environmental effect on the propagated signal, or on empirical models based of large amounts of measured situational data. None of these methods fully capture the actual effect that an environment imparts on a communication signal as it propagates.
This research also modifies the Physical Optics (PO) algorithm utilizing Fourier decomposition to compare the Extended MOMI algorithm to. Both algorithms are applied to propagation scenarios utilizing frequencies in the 1-GHz and 5-GHz bands against a series of signal bandwidths and surface roughnesses. The results are analyzed singularly for Extended-MOMI and against Extended-Physical Optics to better understand the benefits associated with using the Extended-MOMI, the limits of the narrowband approximation, the errors incurred when utilizing a simpler or faster propagation algorithm, and to generally characterize these rough surface propagation channels.
This research also defines and explores which metrics provide the best characterization and utility for communication signal propagation with the additional insights of amplitude-frequency-phase relationships the new algorithm provides. / Doctor of Philosophy / Communication signal propagation, defined as the propagation of signals that have non-zero bandwidths from one point to another, has significant importance in communication signal design, system design, and deployment as well as in spectrum planning applications. Current methods of predicting and analyzing communication signal propagation rely on either using only a single frequency instead of a band of frequencies, stochastic techniques that model the environmental effect on the propagated signal, or on empirical models based of large amounts of measured situational data. None of these methods fully capture the actual effect that an environment imparts on a communication signal as it propagates. A technique that accurately models the environmental effect on propagating communication signals would result in knowledge about a communication signal strength and shape as it passes through the propagation space.
Analyzing communication signals with single frequency propagation algorithms requires assuming all the frequencies that make up the communication signal propagate exactly the same way, an assumption known as the narrowband approximation. It is not known when the narrowband approximation breaks down in various circumstances. Consequently a more rigorous approach needed to be identified to enable a more accurate and complete analysis of communication signals, which is the objective of the research.
This research solves these modeling gaps by modifying a single-frequency electromagnetic propagation analysis technique, the Method of Ordered Multiple Interactions, for use on communication signals and propagation channels. The new algorithm, Extended-MOMI, allows for an examination of communication signal propagation over rough surfaces. This new algorithm incorporates all of the information needed for communication signal propagation analysis; something that is missing from current methods. This technique enables tailored communication signal propagation studies as well as an investigations into when the narrowband assumption is valid and when simpler and faster algorithms could be utilized for a now known increase in error. This research also explores which metrics are best utilized with the additional signal information the new algorithm enables.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/111289 |
| Date | 18 July 2022 |
| Creators | Stockland, Robert Thomas |
| Contributors | Electrical Engineering, Brown, Gary S., Pratt, Timothy, Davis, William A., Reed, Jeffrey H., Kohler, Werner E. |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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