DRIVING AI-NATIVE RAN INNOVATION WITH THE SIONNA RESEARCH KIT
December 2 @ 10:30 am - 11:01 am
DRIVING AI-NATIVE RAN INNOVATION WITH THE SIONNA RESEARCH KIT
Dr. Sebastian Cammerer, Senior Research Scientist, NVIDIA
Registration Link: []<a href="https://events.vtools.ieee.org/m/517965
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Host:”>https://events.vtools.ieee.org/m/517965
Host: IEEE [Saint Maurice Section, CosmSoc chapter COM19](mailto:<a href="http://messaoud.ahmed.ouameur@uqtr.ca?subject=From%20Propagation%20Models%20to%20Physics-Based%20Digital%20Twins%20of%20Emerging%20Wireless%20Communication%20Systems%20-%20Saint%20Maurice%20Sect%20Chap,%20COM19)
When:” target=”_blank” title=”messaoud.ahmed.ouameur@uqtr.ca?subject=From%20Propagation%20Models%20to%20Physics-Based%20Digital%20Twins%20of%20Emerging%20Wireless%20Communication%20Systems%20-%20Saint%20Maurice%20Sect%20Chap,%20COM19)
When:”>messaoud.ahmed.ouameur@uqtr.ca?subject=From%20Propagation%20Models%20to%20Physics-Based%20Digital%20Twins%20of%20Emerging%20Wireless%20Communication%20Systems%20-%20Saint%20Maurice%20Sect%20Chap,%20COM19)
When: December 2nd at 10H30 AM EST
Via zoom: <a href="https://uqtr.zoom.us/j/81521084215?pwd=bchQDndZg7DTlpVuaeag6bhGwaOvn9.1
Meeting” target=”_blank” title=”https://uqtr.zoom.us/j/81521084215?pwd=bchQDndZg7DTlpVuaeag6bhGwaOvn9.1
Meeting”>https://uqtr.zoom.us/j/81521084215?pwd=bchQDndZg7DTlpVuaeag6bhGwaOvn9.1
Meeting ID: 815 2108 4215
Password: 018477
ABSTRACT
AI will become a cornerstone of future wireless communication systems, enabling radio access networks (RANs) that dynamically adapt to specific radio frequency (RF) environments and enhance their performance even after deployment. Novel paradigms such as end-to-end learning for pilotless transmissions and semantic communications add to the transformative potential of AI. Integrating neural network components into the signal processing pipeline of wireless transceivers poses research challenges, particularly in meeting the stringent, often sub-millisecond, inference latency required by RANs. As such, the full potential of AI-native RANs depends on three main factors: (a) the development of robust software tools, (b) the deployment of specialized hardware platforms for real-time AI acceleration, and (c) the design of fundamentally new transceiver <a href="http://algorithms.
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In this talk, we outline a path toward prototyping an AI-native RAN using the Sionna Research Kit—an open-source platform designed for development, training, and deployment of AI-native wireless communication systems. We present a 5G NR-compliant real-time neural receiver connected to commercial user equipment, demonstrating how research ideas can be rapidly transformed into over-the-air prototypes using open-source tools. To foster collaboration and accelerate progress in the field, all experiments and results will be made openly available, lowering the barrier to entry and enabling researchers worldwide to translate their ideas into real-world wireless communication <a href="http://systems.
BIOGRAPHY
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BIOGRAPHY
Dr. Sebastian Cammerer is a Senior Research Scientist at NVIDIA, working at the intersection of wireless communications and machine learning. He is one of the core developers and maintainers of the Sionna open-source link-level simulator. Before joining NVIDIA, he received his PhD in Electrical Engineering and Information Technology from the University of Stuttgart, Germany. His main research interests are machine learning for wireless communications and channel coding. His work has been recognized with several awards, including the VDE ITG Dissertationspreis 2022, the IEEE SPS Young Author Best Paper Award 2019, and third prize in the Nokia Bell Labs Prize 2019.
Speaker(s): Dr. Cammerer,