Modeling of split step parabolic wave equation using the graphics processing unit

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2014
Sekmen, Selin
Electromagnetic (EM) wave propagation is an important phenomenon in modeling radar or communication systems. To develop these kinds of reliable systems, the behavior of EM waves and cases that affect the propagation must be handled correctly. EM waves are strongly affected by atmospheric conditions such as temperature, pressure, and humidity, and by global circulation patterns. When they propagate in troposphere, their energy decreases due to change in medium. Other than natural effects, buildings, non-flat terrains also disturb wave propagation, since these kinds of terrain structures cause EM waves to reflect, refract or diffract while they propagate in their normal paths. The main issue in electromagnetic wave propagation is to compute the propagation factor and path loss. Split Step Parabolic Equation (SSPE) is a commonly used parabolic equation that efficiently models the electromagnetic wave propagation in troposphere. It is a one way forward propagation approach, which models forward waves, and neglects backward ones. It is a highly accurate and a reliable method; however, algorithms that implement this model are computationally intensive. GPUs are developed for visual graphical purposes, however general purpose use of GPUs become popular in the last decades. As methods for electromagnetic modeling are computationally intensive, GPGPUs (General Purpose Graphics Processing Unit) take the attention of people who are interested in electromagnetic wave simulations, as their highly parallel architectures can offer better performance. This thesis focuses on implementation of the Split Step Parabolic Wave Equation on the GPU architecture in 2D and 3D environments. We study implementation and performance analysis of SSPE on three different graphic cards.

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Citation Formats
S. Sekmen, “Modeling of split step parabolic wave equation using the graphics processing unit,” M.S. - Master of Science, Middle East Technical University, 2014.