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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/31582
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dc.contributor.advisorHranilovic, Steve-
dc.contributor.advisorTaylor, Michael-
dc.contributor.authorAkhlaghi, Hamed-
dc.date.accessioned2025-04-29T15:56:41Z-
dc.date.available2025-04-29T15:56:41Z-
dc.date.issued2025-
dc.identifier.urihttp://hdl.handle.net/11375/31582-
dc.description.abstractIn modern space-based networks, growing bandwidth demands and increasing mission complexity drive the need for accurate, high-resolution simulations that capture small-scale turbulence features and rapid satellite movement. By leveraging GPU parallelization, this simulator manages large data volumes and frequent time steps, enabling the modeling of wavefront distortions essential for robust system design, adaptive optics, and performance optimization. This thesis presents a novel, highspeed simulator for optical propagation through dynamic atmospheric turbulence affecting satellite downlinks. The method begins by calculating the effective refractive index structure parameter (C 2 n ) which captures the turbulence strength, along the observation path between the satellite and ground receiver. This derived C 2 n informs the atmospheric slicer, which distributes phase screens throughout the propagation path. The simulation focuses on the first 20 km of atmosphere, where the majority of turbulence affecting free-space optical links occurs. The angular spectrum propagation formula is implemented to achieve Fresnel propagation between planes where phase screens represent integrated turbulence slices at specific altitudes. Temporal evolution is achieved via the frozen flow hypothesis and an adjustable wind model with altitude-dependent wind speeds. Numerical simulation of optical propagation through turbulence with high spatial sampling poses significant computational challenges, especially for rapidly moving Low Earth Orbit (LEO) satellites and simulations with numerous phase screen layers. This work addresses this challenge with an innovative GPU architecture that parallelizes intensive computations and large loops across GPU cores. This advancement enables the use of large phase screens, many layers, and rapid propagation loops, efficiently simulating fast-translating LEO satellites. This comprehensive approach significantly enhances the speed of atmospheric turbulence simulations for satellite communications, offering a powerful tool for system design, performance prediction, and optimization of adaptive optics strategies in free-space optical communication systems. The GPU-accelerated implementation achieves speedup factors of 310× to 600× over conventional CPU-based simulators.en_US
dc.language.isoenen_US
dc.titleGPU-ACCELERATED TURBULENCE SIMULATOR FOR SPACE-BASED OPTICAL COMMUNICATIONSen_US
dc.typeThesisen_US
dc.contributor.departmentElectrical and Computer Engineeringen_US
dc.description.degreetypeThesisen_US
dc.description.degreeMaster of Applied Science (MASc)en_US
dc.description.layabstractOptical satellite communications (SatCom) provides high data throughput and low latency, particularly for low Earth orbit (LEO) satellite applications over distances ranging from 500 to 1,500 km, making them essential for emerging space-based networks. However, due to wind and temperature shifts, atmospheric turbulence severely impacts the quality of downlink channels, necessitating robust simulation tools to inform system design and ensure reliable performance under dynamic conditions. Numerical simulation of optical propagation through turbulence with high spatial sampling poses significant computational challenges, especially for rapidly moving LEO satellites and simulations with a number of phase screen layers. This highresolution sampling is essential for accurately predicting how atmospheric turbulence will affect signal quality, which directly impacts the reliability and performance of these critical communications links. This work addresses this challenge with a Graphic Processing Unit (GPU) architecture that parallelizes intensive computations and large loops across GPU cores. This advancement enables the use of large phase screens, many layers, and rapid propagation loops, efficiently simulating fast-translating LEO satellites. This approach significantly enhances the speed of atmospheric turbulence simulations for satellite communications, offering a powerful tool for system design, performance prediction, and optimization of adaptive optics strategies in free-space optical communication systems. The simulator employs a multi-layered approach to optical propagation, accounting for varying wind speeds and satellite elevation angles to create a comprehensive path simulation of wavefront degradation. The speed and accuracy of the simulator also make it ideal for machine learning applications, generating large datasets of realistic turbulent wavefronts matching atmospheric theory. Validation results demonstrate excellent agreement between theoretical predictions and simulated outputs across various atmospheric conditions and satellite positions. Performance benchmarks show that GPU-accelerated implementation achieves up to 600 times faster execution time within the same conditions compared to a publicly available optical turbulence simulator intended for astronomy, while maintaining equivalent accuracy. This simulator introduces a GPU-accelerated, multi-layer architecture that captures both fast orbital motion and fine-scale atmospheric distortion.en_US
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