Sionna Research Kit: A GPU-Accelerated Research Platform for AI-RAN
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866918029799981056 |
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| author | Cammerer, Sebastian Marcus, Guillermo Zirr, Tobias Aoudia, Fayçal Aït Maggi, Lorenzo Hoydis, Jakob Keller, Alexander |
| author_facet | Cammerer, Sebastian Marcus, Guillermo Zirr, Tobias Aoudia, Fayçal Aït Maggi, Lorenzo Hoydis, Jakob Keller, Alexander |
| contents | We introduce the NVIDIA Sionna Research Kit, a GPU-accelerated research platform for developing and testing AI/ML algorithms in 5G NR cellular networks. Powered by the NVIDIA Jetson AGX Orin, the platform leverages accelerated computing to deliver high throughput and real-time signal processing, while offering the flexibility of a software-defined stack. Built on OpenAirInterface (OAI), it unlocks a broad range of research opportunities. These include developing 5G NR and ORAN compliant algorithms, collecting real-world data for AI/ML training, and rapidly deploying innovative solutions in a very affordable testbed. Additionally, AI/ML hardware acceleration promotes the exploration of use cases in edge computing and AI radio access networks (AI-RAN). To demonstrate the capabilities, we deploy a real-time neural receiver - trained with NVIDIA Sionna and using the NVIDIA TensorRT library for inference - in a 5G NR cellular network using commercial user equipment. The code examples will be made publicly available, enabling researchers to adopt and extend the platform for their own projects. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_15848 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Sionna Research Kit: A GPU-Accelerated Research Platform for AI-RAN Cammerer, Sebastian Marcus, Guillermo Zirr, Tobias Aoudia, Fayçal Aït Maggi, Lorenzo Hoydis, Jakob Keller, Alexander Networking and Internet Architecture Information Theory We introduce the NVIDIA Sionna Research Kit, a GPU-accelerated research platform for developing and testing AI/ML algorithms in 5G NR cellular networks. Powered by the NVIDIA Jetson AGX Orin, the platform leverages accelerated computing to deliver high throughput and real-time signal processing, while offering the flexibility of a software-defined stack. Built on OpenAirInterface (OAI), it unlocks a broad range of research opportunities. These include developing 5G NR and ORAN compliant algorithms, collecting real-world data for AI/ML training, and rapidly deploying innovative solutions in a very affordable testbed. Additionally, AI/ML hardware acceleration promotes the exploration of use cases in edge computing and AI radio access networks (AI-RAN). To demonstrate the capabilities, we deploy a real-time neural receiver - trained with NVIDIA Sionna and using the NVIDIA TensorRT library for inference - in a 5G NR cellular network using commercial user equipment. The code examples will be made publicly available, enabling researchers to adopt and extend the platform for their own projects. |
| title | Sionna Research Kit: A GPU-Accelerated Research Platform for AI-RAN |
| topic | Networking and Internet Architecture Information Theory |
| url | https://arxiv.org/abs/2505.15848 |