Thesis (M.S.)--West Virginia University, 2006. / Title from document title page. Document formatted into pages; contains vii, 85 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 70-72).

Thesis (Ph. D.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains v, 137 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 126-137).

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2007. / Includes bibliographical references (leaves 94-106). Also available in electronic version.

Thesis (Ph. D.)--Ohio State University, 1986. / Includes bibliographical references (leaves 297-301). Available online via OhioLINK's ETD Center

Thesis (M.S.)--Baylor University, 2006. / Includes bibliographical references (p. 80-83).

Thesis (M.S.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains viii, 90 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 74-76).

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The overall growth in cellular, fixed and satellite communications markets, has exceeded many expectations and there is a widespread anticipation that the demand for wireless telecommunication systems will continue to expand in the foreseeable future. Such systems rely in their planning, design and implementation on the availability of radiowave propagation models. In the particular case of land mobile radio systems and wireless fixed access systems, obstacles in the form of vegetation volumes, e.g formations of trees, are likely to influence radio propagation, giving rise to absorption and scattering of radio signals. In this context, this thesis investigates suitable techniques to characterise and model the effects of inhomogeneous volumes of vegetation on the propagation modes of radiowaves. The thesis proposes an enhanced model based on the Radiative Energy Transfer theory (RET) which was discretised to accommodate forests formed by different vegetation species with their distinct propagation characteristics. The discretised model computational structure, comprises several element cells, whose characteristic propagation parameters may be assigned independently. The discretised RET (dRET), is therefore capable of gathering the interactive responses between the element cells comprising the computational structure, leading to the determination of the received signal inside or around a given illuminated vegetation medium. The performance of the proposed model, was assessed utilising results from an extended range of measurements, carried out in different environments. Such measurements comprised those necessary for the model input parameters extraction. Others enabled the model assessment through comparison between the model predictions and the actual directional profile of the measured received signal results. An initial assessment of the model was carried out in the laboratory, using an idealised test forest formation placed inside an anechoic chamber, whereas the final model assessment was performed in an outdoor tree groupings formed by several different full size trees. Both indoor and outdoor measurements, confirmed good overall model performance and predictions of both absorption and scattering propagation modes caused by the presence of vegetation in the radio path. This was demonstrated at micro- and millimetre wave frequency bands, centered at 11.2, 20, 40 and 62.4 GHz frequencies. The thesis provides a valid tested method to evaluate the dRET propagation parameters for various isolated volumes of vegetation. Such parameters, may subsequently be utilized into the proposed propagation model, which is shown to be capable of dealing with typical and non homogeneous forests thereby effectively predicting the received signal directional profile at several locations inside and around the inhomogeneous forest. The thesis has many novel features. These include the development and extension of the basic dRET model removing many limitations. The parameter extraction including the effects of the receive antenna radiation pattern is another novel contribution. Further novelty lies in the application of the dRET model to mixed, finite and inhomogeneous vegetation formations. As a result of these refinements and extensions, the dRET propagation model has been shown to yield predicted results which agree well with measurements.

The ever growing application of wireless communication systems requires accurate models for characterising radiowave propagation when affected by the presence of a variety of obstacles. In particular if the obstacles take the shape of vegetation volumes, like single trees or groups of trees and are present in the radio path, they give rise to absorption and scattering of radio signals. This thesis presents a literature review of common models for radiowave propagation through vegetation, the theory of Radiative Energy Transfer (RET) is one of these models and provides an accurate analysis of radiowave propagation through a vegetation media. Extensive measurements have been designed and conducted in a controlled indoor environment to provide valuable measurement data for later development of deconvolution approaches. It can be shown that the measured directional spectra are convolution products of the phase function pattern and the receiver antenna radiation patterns, which impacts determination of the RET input parameters. Consequently, in order to achieve more accurate determination of the RET input parameters, the adverse influence caused by receiver antenna radiation patterns have to be removed from measured directional spectra by implementing a process of deconvolution. This thesis provides successful implementation of two iterative based deconvolution techniques on the measurement directional spectra. To the author's knowledge, this is its first kind of application to eliminate distortion caused by the receiver antenna radiation pattern during measurements. This thesis reports a number of novel approaches. These include the further development and extension of deconvolution techniques such as combining the Bennia-Riad criterion and an error function to determine optimal parameters, as well as using pre-filtering techniques to improve the deconvolution results. Development of clearly defined criteria based on the knowledge of the central-limit theorem and discussion of loss of information avoidance during convolution is another novel contribution. Further novelty lies in the modification of the two methods to suit implementation on the measurement data from radiowaves impacting on vegetation volumes. As a result of these refinements, extracted RET input parameters from the restored patterns after applying the deconvolution processes show evident improvements compared to those extracted from directly measured patterns. Early stage results of this project are published in the IEEE Proceedings on Next Generation Applications, Services and Technologies.