Sionna Research Kit: A GPU-Accelerated Research Platform for AI-RAN
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) [1], 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.
Authors
- Alexander Keller (ORCID: https://orcid.org/0000-0001-5716-3634)
- Fayçal Aït Aoudia (ORCID: https://orcid.org/0000-0002-8905-1669)
- Sebastian Cammerer (ORCID: https://orcid.org/0000-0002-7614-5156)
- Tobias Zirr (ORCID: https://orcid.org/0009-0003-1091-3858)
- Guillermo Marcus (ORCID: https://orcid.org/0000-0003-4270-4359)
- Jakob Hoydis (ORCID: https://orcid.org/0000-0002-0438-967X)
- Lorenzo Maggi (ORCID: https://orcid.org/0000-0003-3643-8349)
Publication Details
- Published
- 2025-05-26
- DOI
- https://doi.org/10.1109/icmlcn64995.2025.11140427
- Citations
- 1
- Primary Topic
- Wireless Signal Modulation Classification
- Type
- article
- Field-Weighted Citation Impact
- 2.48