Abstract
This article investigates the prediction accuracy of an advanced deterministic propagation model in terms of channel depolarization and frequency selectivity for indoor wireless propagation. In addition to specular reflection and diffraction, the developed ray tracing tool considers penetration through dielectric blocks and/or diffuse scattering mechanisms. The sensitivity and prediction accuracy analysis is based on two measurement campaigns carried out in a warehouse and an office building. It is shown that the implementation of diffuse scattering into RT significantly increases the accuracy of the cross-polar discrimination prediction, whereas the delay-spread prediction is only marginally improved.
Highlights
The characterization of wireless propagation channels may rely either on stochastic or deterministic models [1]
The simulated 3D environment is created taking into account constituent parts of buildings and major objects present in the scenario (i. e., the containers in warehouse scenario and doors and desks in the office scenario)
The results show that including scattering does not improve significantly the prediction accuracy, except in the last three positions, which can described as deep NLOS, where ray tracing (RT) without scattering fails to predict any ray, or a significant number of rays, arriving at the Rx
Summary
The characterization of wireless propagation channels may rely either on stochastic or deterministic models [1]. When site-specific predictions are required, the choice often falls on deterministic models [2], e.g., raybased techniques. Ray tracing (RT) is a geometrical optics approach that evaluates all paths followed by rays as they interact with the environment. It has been successfully used for many years for macro and microcellular channel modeling. Wireless systems have continuously evolved, implying that models should evolve too. While a classical deterministic model may have proved accurate for relatively narrowband cellular systems, this might not hold true when dealing with the application-oriented systems exploiting multiple dimensions (space, polarization, frequency, etc.)
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