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

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sionna Research Kit: A GPU-Accelerated Research Platform for AI-RAN

Alexander Keller, Fayçal Aït Aoudia, Sebastian Cammerer, Tobias Zirr et al.
1 citations
Wireless Signal Modulation Classification
2.48
article

Sionna Research Kit: A GPU-Accelerated Research Platform for AI-RAN

Alexander Keller, Fayçal Aït Aoudia, Sebastian Cammerer, Tobias Zirr, Guillermo Marcus, Jakob Hoydis, Lorenzo Maggi
article en
1 citations

Abstract

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.

Openalex Percentile: Top 9%
Wireless Signal Modulation Classification
2.48
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Sionna Research Kit: A GPU-Accelerated Research Platform for AI-RAN — Alexander Keller, Fayçal Aït Aoudia, et al. · (2025) | TGRS Research Map | TGRS