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Proceedings Paper

Influence of electrical parameters on three-dimensional ray-tracing-based predictions in complex indoor environments
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Paper Abstract

A three-dimensional (3D) ray-tracing model with the use of the uniform theory of diffraction and geometrical optics in which multiple reflections and diffractions are considered is presented in this paper to predict the channel coverage prediction of indoor environments, such as the received power and the RMS delay spread. The prediction model requires databases for the buildings and the objects layout in the indoor environment, in which the electrical characteristics (permittivity, conductivity, etc.) must be included. Electrical parameters directly influence the calculation of the reflection and diffraction phenomena. However, one cannot easily derive the electrical parameters due to the complexity of real building walls and the indoor objects. As a result, it is of great interest to quantify the prediction errors as functions of the electrical parameters inaccuracies. The Fresnel reflection coefficient and the diffraction coefficient are considered assuming several values in two different methods. The first method is to change the permittivity or the conductivity of the internal wall, the ceiling and the floor at the same time. The other method is to change the permittivity or the conductivity of the indoor objects while keep the electrical parameters of the internal wall, the ceiling and the floor unchanged. The mean error and standard deviation between predictions results of the original database and the error database are presented and analyzed. It is found that the accuracy of the model is sensitive to the relative permittivity and conductivity, and the sensitivity study also leads to the improvement of the accuracy of 3D ray-tracing model in indoor environments.

Paper Details

Date Published: 18 November 2014
PDF: 7 pages
Proc. SPIE 9263, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications V, 926325 (18 November 2014); doi: 10.1117/12.2069170
Show Author Affiliations
Li-Xin Guo, Xidian Univ. (China)
Chang-Long Li, Xidian Univ. (China)
Zhong-Yu Liu, Xidian Univ. (China)


Published in SPIE Proceedings Vol. 9263:
Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications V
Allen M. Larar; Makoto Suzuki; Jianyu Wang, Editor(s)

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