Anxel Beam Shrinkage Method and Heterogeneous Computing-Accelerated Full-Image Theory Method Ray Tracing Enabling Massive Outdoor Propagation Modeling

Despite their accuracy, traditional image theory (IT) ray tracers were previously limited to basic simulation environments with fewer field observation points (FOPs) and lower ray bounce orders due to computational inefficiencies. In this study, we propose a novel full-3-D anxel beam shrinkage (ABS)...

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Vydané v:IEEE transactions on antennas and propagation Ročník 72; číslo 7; s. 5935 - 5949
Hlavní autori: Kim, Yongwan, Yang, Hyunjun, Kim, Hooyoung, Jo, Junpyo, Oh, Jungsuek
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.07.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Abstract Despite their accuracy, traditional image theory (IT) ray tracers were previously limited to basic simulation environments with fewer field observation points (FOPs) and lower ray bounce orders due to computational inefficiencies. In this study, we propose a novel full-3-D anxel beam shrinkage (ABS) method and heterogeneous computing-accelerated full-IT method ray-tracing (RT) framework enabling massive outdoor propagation modeling. The proposed framework is divided into three components: 1) visibility preprocessing; 2) visibility tree generation, which introduces a novel ABS method to expedite the creation process and minimize the visibility tree's size; and 3) shadow testing and field calculation, incorporating a heterogeneous computing algorithm designed to efficiently manage numerous FOPs. We also demonstrated that the proposed framework, utilizing both central processing unit (CPU) and graphical processing unit (GPU) parallel computing, is 651 times faster than the IT method solver of WinProp, which supports only CPU parallel computing. Furthermore, it is confirmed that the proposed RT framework can handle <inline-formula> <tex-math notation="LaTeX">1\times 1 </tex-math></inline-formula> km wide and dense urban outdoor simulation with up to the maximum ray bouncing order of 6 and thousands of FOPs. The proposed RT framework could serve as a foundation for future advancements in IT method RT techniques in complex and massive scenarios, which were previously exclusive to the shooting and bouncing rays method ray tracers.
AbstractList Despite their accuracy, traditional image theory (IT) ray tracers were previously limited to basic simulation environments with fewer field observation points (FOPs) and lower ray bounce orders due to computational inefficiencies. In this study, we propose a novel full-3-D anxel beam shrinkage (ABS) method and heterogeneous computing-accelerated full-IT method ray-tracing (RT) framework enabling massive outdoor propagation modeling. The proposed framework is divided into three components: 1) visibility preprocessing; 2) visibility tree generation, which introduces a novel ABS method to expedite the creation process and minimize the visibility tree's size; and 3) shadow testing and field calculation, incorporating a heterogeneous computing algorithm designed to efficiently manage numerous FOPs. We also demonstrated that the proposed framework, utilizing both central processing unit (CPU) and graphical processing unit (GPU) parallel computing, is 651 times faster than the IT method solver of WinProp, which supports only CPU parallel computing. Furthermore, it is confirmed that the proposed RT framework can handle <inline-formula> <tex-math notation="LaTeX">1\times 1 </tex-math></inline-formula> km wide and dense urban outdoor simulation with up to the maximum ray bouncing order of 6 and thousands of FOPs. The proposed RT framework could serve as a foundation for future advancements in IT method RT techniques in complex and massive scenarios, which were previously exclusive to the shooting and bouncing rays method ray tracers.
Despite their accuracy, traditional image theory (IT) ray tracers were previously limited to basic simulation environments with fewer field observation points (FOPs) and lower ray bounce orders due to computational inefficiencies. In this study, we propose a novel full-3-D anxel beam shrinkage (ABS) method and heterogeneous computing-accelerated full-IT method ray-tracing (RT) framework enabling massive outdoor propagation modeling. The proposed framework is divided into three components: 1) visibility preprocessing; 2) visibility tree generation, which introduces a novel ABS method to expedite the creation process and minimize the visibility tree’s size; and 3) shadow testing and field calculation, incorporating a heterogeneous computing algorithm designed to efficiently manage numerous FOPs. We also demonstrated that the proposed framework, utilizing both central processing unit (CPU) and graphical processing unit (GPU) parallel computing, is 651 times faster than the IT method solver of WinProp, which supports only CPU parallel computing. Furthermore, it is confirmed that the proposed RT framework can handle [Formula Omitted] km wide and dense urban outdoor simulation with up to the maximum ray bouncing order of 6 and thousands of FOPs. The proposed RT framework could serve as a foundation for future advancements in IT method RT techniques in complex and massive scenarios, which were previously exclusive to the shooting and bouncing rays method ray tracers.
Author Jo, Junpyo
Yang, Hyunjun
Kim, Yongwan
Oh, Jungsuek
Kim, Hooyoung
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Snippet Despite their accuracy, traditional image theory (IT) ray tracers were previously limited to basic simulation environments with fewer field observation points...
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SubjectTerms Accuracy
Algorithms
Asymptotic high-frequency techniques
Bouncing
Central Processing Unit
Central processing units
Computational modeling
CPUs
Diffraction
graphical processing unit (GPU)
Graphics processing units
image theory (IT) ray tracing (RT)
Parallel processing
Ray tracing
Reflection
shooting and bouncing ray (SBR) techniques
Shrinkage
Tracers
Visibility
wireless propagation modeling
Title Anxel Beam Shrinkage Method and Heterogeneous Computing-Accelerated Full-Image Theory Method Ray Tracing Enabling Massive Outdoor Propagation Modeling
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