Thesis (M.S.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 1998. / Includes bibliographical references (leaves 63-64).

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Our related research review on propagation models reveals six factors that are significant in last mile connectivity via LAP: path loss, elevation angle, LAP altitude, coverage area, power consumption, operation frequency, interference, and antenna type. These factors can help with monitoring system performance, network planning, coverage footprint, receivers' line-of-sight, quality of service requirements, and data rates which may all vary in response to geomorphology characteristics. Several competing propagation models have been proposed over the years but whilst they collectively raise many shortcomings such as limited altitude up to few tens of meters, lack of cover across different environments, low perdition accuracy they also exhibit several advantages. Four propagation models, which are representatives of their types, have been selected since they exhibit advantages in relation to high altitude, wide coverage range, adaption across different terrains. In addition, all four have been extensively deployed in the past and as a result their correction factors have evolved over the years to yield extremely accurate results which makes the development and evaluation aspects of this research very precise. The four models are: ITU-R P.529-3, Okumura, Hata-Davidson, and ATG. The aim of this doctoral research is to design a new propagation model for last-mile connectivity using LAPs technology as an alternative to aerial base station that includes all six factors but does not exhibit any of the shortcomings of existing models. The new propagation model evolves from existing models using machine learning. The four models are first adapted to include the elevation angle alongside the multiple-input multiple-output diversity gain, our first novelty in propagation modelling. The four adapted models are then used as input in a Neural Network framework and their parameters are clustered in a Self-Organizing-Map using a minimax technique. The framework evolves an optimal propagation model that represents the main research contribution of this research. The optimal propagation model is deployed in two proof-of-concept applications, a wireless sensor network, and a cellular structure. The performance of the optimal model is evaluated and then validated against that of the four adapted models first in relation to predictions reported in the literature and then in the context of the two proof-of-concept applications. The predictions of the optimised model are significantly improved in comparison to those of the four adapted propagation models. Each of the two proof-of-concept applications also represent a research novelty.

Thesis (Ph. D.)--Brigham Young University. Dept. of Electrical and Computer Engineering. / Includes bibliographical references (p. 199-206).

Thesis (M.S.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2004. / Includes bibliographical references (p. 75-77).

Sparse military satellite constellations were designed using two methods: a traditional approach and a genetic algorithm. One of the traditional constellation designs was the Discoverer II space based radar. Discoverer II was an 8 plane, 24 satellite, Low Earth Orbit (LEO), Walker constellation designed to provide high-range resolution ground moving target indication (HRR-GMTI), synthetic aperture radar (SAR) imaging and high resolution digital terrain mapping. The traditional method designed 9-ball, 12-ball, 18-ball, and 24- ball Walker constellations. The genetic algorithm created constellations by deriving a phenotype from a triploid genotype encoding of orbital elements. The performance of both design methods were compared using a computer simulation. The fitness of each constellation was calculated using maximum gap time, maximum revisit time, and percent coverage. The goal was to determine if one design method would consistently outperform the other. The genetic algorithm offered a fitness improvement over traditional constellation design methods in all cases except the 24-ball constellation where it demonstrated comparable results. The genetic algorithm improvement over the traditional constellations increased as the number of satellites per constellation decreased. A derived equation related revisit time to the number of ship tracks maintained. / US Navy (USN) author.

Thesis (M.S.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2003. / Includes bibliographical references (p. 103-104).

Thesis (M.S. in Space Systems Operations)--Naval Postgraduate School, September 2004. / Thesis advisor(s): Charles Racoosin. Includes bibliographical references (p. 85-87). Also available online.

Thesis (M.S.)--Brigham Young University. Dept. of Electrical and Computer Engineering, 2006. / Includes bibliographical references (p. 83-85).

Thesis (M.S.) -- Brigham Young University. Dept. of Electrical and Computer Engineering, 2002. / Includes bibliographical references (p. 99-103).