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UID:68EA708A-721B-430C-8188-077F4C34AFE2
DTSTART;TZID=America/New_York:20251202T103000
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DESCRIPTION:DRIVING AI-NATIVE RAN INNOVATION WITH THE SIONNA RESEARCH KIT\n
 \nDr. Sebastian Cammerer\, Senior Research Scientist\, NVIDIA\n\nRegistrat
 ion Link: []https://events.vtools.ieee.org/m/517965\n\nHost: IEEE [Saint M
 aurice Section\, CosmSoc chapter COM19](mailto:messaoud.ahmed.ouameur@uqtr
 .ca?subject=From%20Propagation%20Models%20to%20Physics-Based%20Digital%20T
 wins%20of%20Emerging%20Wireless%20Communication%20Systems%20-%20Saint%20Ma
 urice%20Sect%20Chap\,%20COM19)\n\nWhen: December 2nd at 10H30 AM EST\n\nVi
 a zoom: https://uqtr.zoom.us/j/81521084215?pwd=bchQDndZg7DTlpVuaeag6bhGwaO
 vn9.1\n\nMeeting ID: 815 2108 4215\n\nPassword: 018477\n\nABSTRACT\n\nAI w
 ill become a cornerstone of future wireless communication systems\, enabli
 ng radio access networks (RANs) that dynamically adapt to specific radio f
 requency (RF) environments and enhance their performance even after deploy
 ment. Novel paradigms such as end-to-end learning for pilotless transmissi
 ons 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 meet
 ing 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 deploymen
 t of specialized hardware platforms for real-time AI acceleration\, and (c
 ) the design of fundamentally new transceiver algorithms.\n\nIn this talk\
 , we outline a path toward prototyping an AI-native RAN using the Sionna R
 esearch 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 eq
 uipment\, 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 resear
 chers worldwide to translate their ideas into real-world wireless communic
 ation systems.\n\nBIOGRAPHY\n\nDr. Sebastian Cammerer is a Senior Research
  Scientist at NVIDIA\, working at the intersection of wireless communicati
 ons and machine learning. He is one of the core developers and maintainers
  of the Sionna open-source link-level simulator. Before joining NVIDIA\, h
 e received his PhD in Electrical Engineering and Information Technology fr
 om 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 Dissertati
 onspreis 2022\, the IEEE SPS Young Author Best Paper Award 2019\, and thir
 d prize in the Nokia Bell Labs Prize 2019.\n\nSpeaker(s): Dr. Cammerer\, \
 n\nVirtual: https://events.vtools.ieee.org/m/517965
LOCATION:Virtual: https://events.vtools.ieee.org/m/517965
ORGANIZER:messaoud.ahmed.ouameur@uqtr.ca
SEQUENCE:6
SUMMARY:DRIVING AI-NATIVE RAN INNOVATION WITH THE SIONNA RESEARCH KIT
URL;VALUE=URI:https://events.vtools.ieee.org/m/517965
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;&lt;strong&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font-siz
 e: 14.0pt\; line-height: 107%\; font-family: &#39;Adobe Devanagari&#39;\,serif\; m
 so-fareast-font-family: Calibri\; mso-fareast-theme-font: minor-latin\; ms
 o-ansi-language: EN-CA\; mso-fareast-language: EN-US\; mso-bidi-language: 
 AR-SA\;&quot;&gt;DRIVING AI-NATIVE RAN INNOVATION WITH THE SIONNA RESEARCH KIT&lt;/sp
 an&gt;&lt;/strong&gt;&lt;/p&gt;\n&lt;p&gt;&lt;strong&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font-size: 14.0pt\;
  line-height: 107%\; font-family: &#39;Adobe Devanagari&#39;\,serif\; mso-fareast-
 font-family: Calibri\; mso-fareast-theme-font: minor-latin\; mso-ansi-lang
 uage: EN-CA\; mso-fareast-language: EN-US\; mso-bidi-language: AR-SA\;&quot;&gt;&lt;s
 pan lang=&quot;EN-CA&quot; style=&quot;font-size: 12.0pt\; line-height: 107%\; font-famil
 y: &#39;Adobe Devanagari&#39;\,serif\;&quot;&gt;Dr. Sebastian Cammerer\,&amp;nbsp\;&lt;/span&gt;&lt;spa
 n lang=&quot;EN-CA&quot; style=&quot;font-size: 12.0pt\; line-height: 107%\; font-family:
  &#39;Adobe Devanagari&#39;\,serif\;&quot;&gt;Senior Research Scientist\, NVIDIA&lt;/span&gt;&lt;/s
 pan&gt;&lt;/strong&gt;&lt;/p&gt;\n&lt;p class=&quot;MsoNormal&quot; style=&quot;text-align: justify\;&quot;&gt;&lt;str
 ong style=&quot;mso-bidi-font-weight: normal\;&quot;&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font-
 size: 12.0pt\; line-height: 107%\; font-family: &#39;Adobe Devanagari&#39;\,serif\
 ; color: #00b0f0\; background: lightgrey\; mso-highlight: lightgrey\;&quot;&gt;Reg
 istration Link:&lt;/span&gt;&lt;/strong&gt;&lt;strong style=&quot;mso-bidi-font-weight: normal
 \;&quot;&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font-size: 12.0pt\; line-height: 107%\; font
 -family: &#39;Adobe Devanagari&#39;\,serif\; color: #00b0f0\;&quot;&gt; &lt;a name=&quot;_Hlk21210
 9880&quot;&gt;&lt;/a&gt;https://events.vtools.ieee.org/m/517965&lt;/span&gt;&lt;/strong&gt;&lt;/p&gt;\n&lt;p 
 class=&quot;MsoNormal&quot; style=&quot;text-align: justify\;&quot;&gt;&lt;strong style=&quot;mso-bidi-fo
 nt-weight: normal\;&quot;&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font-size: 12.0pt\; line-he
 ight: 107%\; font-family: &#39;Adobe Devanagari&#39;\,serif\; color: #00b0f0\; bac
 kground: lightgrey\; mso-highlight: lightgrey\;&quot;&gt;Host:&lt;/span&gt;&lt;/strong&gt;&lt;str
 ong style=&quot;mso-bidi-font-weight: normal\;&quot;&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font-
 size: 12.0pt\; line-height: 107%\; font-family: &#39;Adobe Devanagari&#39;\,serif\
 ; color: #00b0f0\;&quot;&gt; IEEE &lt;/span&gt;&lt;/strong&gt;&lt;span lang=&quot;EN-CA&quot;&gt;&lt;a href=&quot;mail
 to:messaoud.ahmed.ouameur@uqtr.ca?subject=From%20Propagation%20Models%20to
 %20Physics-Based%20Digital%20Twins%20of%20Emerging%20Wireless%20Communicat
 ion%20Systems%20-%20Saint%20Maurice%20Sect%20Chap\,%20COM19&quot;&gt;&lt;span style=&quot;
 color: #00b0f0\; text-decoration: none\; text-underline: none\;&quot;&gt;Saint Mau
 rice Section\, CosmSoc chapter COM19&lt;/span&gt;&lt;/a&gt;&lt;/span&gt;&lt;/p&gt;\n&lt;p class=&quot;MsoN
 ormal&quot; style=&quot;text-align: justify\;&quot;&gt;&lt;strong style=&quot;mso-bidi-font-weight: 
 normal\;&quot;&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font-size: 12.0pt\; line-height: 107%\
 ; font-family: &#39;Adobe Devanagari&#39;\,serif\; color: #00b0f0\; background: li
 ghtgrey\; mso-highlight: lightgrey\;&quot;&gt;When:&lt;/span&gt;&lt;/strong&gt;&lt;strong style=&quot;
 mso-bidi-font-weight: normal\;&quot;&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font-size: 12.0p
 t\; line-height: 107%\; font-family: &#39;Adobe Devanagari&#39;\,serif\; color: #0
 0b0f0\;&quot;&gt; December 2nd at 10H30 AM EST&lt;/span&gt;&lt;/strong&gt;&lt;/p&gt;\n&lt;p class=&quot;MsoN
 ormal&quot; style=&quot;margin-bottom: 0cm\; text-align: justify\;&quot;&gt;&lt;strong style=&quot;m
 so-bidi-font-weight: normal\;&quot;&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font-size: 12.0pt
 \; line-height: 107%\; font-family: &#39;Adobe Devanagari&#39;\,serif\; color: #00
 b0f0\; background: lightgrey\; mso-highlight: lightgrey\;&quot;&gt;Via zoom:&lt;/span
 &gt;&lt;/strong&gt;&lt;strong style=&quot;mso-bidi-font-weight: normal\;&quot;&gt;&lt;span lang=&quot;EN-CA
 &quot; style=&quot;font-size: 12.0pt\; line-height: 107%\; font-family: &#39;Adobe Devan
 agari&#39;\,serif\; color: #00b0f0\;&quot;&gt; &lt;/span&gt;&lt;/strong&gt;&lt;span lang=&quot;EN-CA&quot;&gt;&lt;a h
 ref=&quot;https://uqtr.zoom.us/j/81521084215?pwd=bchQDndZg7DTlpVuaeag6bhGwaOvn9
 .1&quot;&gt;&lt;strong style=&quot;mso-bidi-font-weight: normal\;&quot;&gt;&lt;span style=&quot;font-size:
  12.0pt\; line-height: 107%\; font-family: &#39;Adobe Devanagari&#39;\,serif\; col
 or: #00b0f0\;&quot;&gt;https://uqtr.zoom.us/j/81521084215?pwd=bchQDndZg7DTlpVuaeag
 6bhGwaOvn9.1&lt;/span&gt;&lt;/strong&gt;&lt;/a&gt;&lt;/span&gt;&lt;/p&gt;\n&lt;p class=&quot;MsoNormal&quot; style=&quot;m
 argin-bottom: 0cm\; text-align: justify\;&quot;&gt;&lt;strong style=&quot;mso-bidi-font-we
 ight: normal\;&quot;&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font-size: 12.0pt\; line-height:
  107%\; font-family: &#39;Adobe Devanagari&#39;\,serif\; color: #00b0f0\; backgrou
 nd: lightgrey\; mso-highlight: lightgrey\;&quot;&gt;Meeting ID:&lt;/span&gt;&lt;/strong&gt;&lt;st
 rong style=&quot;mso-bidi-font-weight: normal\;&quot;&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font
 -size: 12.0pt\; line-height: 107%\; font-family: &#39;Adobe Devanagari&#39;\,serif
 \; color: #00b0f0\;&quot;&gt; 815 2108 4215&lt;/span&gt;&lt;/strong&gt;&lt;/p&gt;\n&lt;p class=&quot;MsoNorm
 al&quot; style=&quot;margin-bottom: 0cm\; text-align: justify\;&quot;&gt;&lt;strong style=&quot;mso-
 bidi-font-weight: normal\;&quot;&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font-size: 12.0pt\; 
 line-height: 107%\; font-family: &#39;Adobe Devanagari&#39;\,serif\; color: #00b0f
 0\; background: lightgrey\; mso-highlight: lightgrey\;&quot;&gt;Password:&lt;/span&gt;&lt;/
 strong&gt;&lt;strong style=&quot;mso-bidi-font-weight: normal\;&quot;&gt;&lt;span lang=&quot;EN-CA&quot; s
 tyle=&quot;font-size: 12.0pt\; line-height: 107%\; font-family: &#39;Adobe Devanaga
 ri&#39;\,serif\; color: #00b0f0\;&quot;&gt; 018477&lt;/span&gt;&lt;/strong&gt;&lt;/p&gt;\n&lt;p class=&quot;MsoN
 ormal&quot; style=&quot;text-align: justify\;&quot;&gt;&lt;strong&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;fon
 t-size: 12.0pt\; line-height: 107%\; font-family: &#39;Adobe Devanagari&#39;\,seri
 f\;&quot;&gt;ABSTRACT &lt;/span&gt;&lt;/strong&gt;&lt;/p&gt;\n&lt;p class=&quot;MsoNormal&quot; style=&quot;text-align
 : justify\;&quot;&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font-size: 12.0pt\; line-height: 10
 7%\; font-family: &#39;Adobe Devanagari&#39;\,serif\;&quot;&gt;AI will become a cornerston
 e of future wireless communication systems\, enabling radio access network
 s (RANs) that dynamically adapt to specific radio frequency (RF) environme
 nts and enhance their performance even after deployment. Novel paradigms s
 uch as end-to-end learning for pilotless transmissions and semantic commun
 ications add to the transformative potential of AI. Integrating neural net
 work components into the signal processing pipeline of wireless transceive
 rs poses research challenges\, particularly in meeting the stringent\, oft
 en sub-millisecond\, inference latency required by RANs. As such\, the ful
 l potential of AI-native RANs depends on three main factors: (a) the devel
 opment of robust software tools\, (b) the deployment of specialized hardwa
 re platforms for real-time AI acceleration\, and (c) the design of fundame
 ntally new transceiver algorithms. &lt;/span&gt;&lt;/p&gt;\n&lt;p class=&quot;MsoNormal&quot; style
 =&quot;text-align: justify\;&quot;&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font-size: 12.0pt\; lin
 e-height: 107%\; font-family: &#39;Adobe Devanagari&#39;\,serif\;&quot;&gt;In this talk\, 
 we outline a path toward prototyping an AI-native RAN using the Sionna Res
 earch Kit&amp;mdash\;an open-source platform designed for development\, traini
 ng\, and deployment of AI-native wireless communication systems. We presen
 t a 5G NR-compliant real-time neural receiver connected to commercial user
  equipment\, demonstrating how research ideas can be rapidly transformed i
 nto over-the-air prototypes using open-source tools. To foster collaborati
 on and accelerate progress in the field\, all experiments and results will
  be made openly available\, lowering the barrier to entry and enabling res
 earchers worldwide to translate their ideas into real-world wireless commu
 nication systems.&lt;/span&gt;&lt;/p&gt;\n&lt;p class=&quot;MsoNormal&quot; style=&quot;text-align: just
 ify\;&quot;&gt;&lt;strong style=&quot;mso-bidi-font-weight: normal\;&quot;&gt;&lt;span lang=&quot;EN-CA&quot; s
 tyle=&quot;font-size: 12.0pt\; line-height: 107%\; font-family: &#39;Adobe Devanaga
 ri&#39;\,serif\;&quot;&gt;BIOGRAPHY&lt;/span&gt;&lt;/strong&gt;&lt;/p&gt;\n&lt;p class=&quot;MsoNormal&quot; style=&quot;t
 ext-align: justify\;&quot;&gt;&lt;strong&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font-size: 12.0pt\
 ; line-height: 107%\; font-family: &#39;Adobe Devanagari&#39;\,serif\;&quot;&gt;Dr. Sebast
 ian Cammerer&lt;/span&gt;&lt;/strong&gt;&lt;span lang=&quot;EN-CA&quot; style=&quot;font-size: 12.0pt\; 
 line-height: 107%\; font-family: &#39;Adobe Devanagari&#39;\,serif\;&quot;&gt; is a Senior
  Research Scientist at NVIDIA\, working at the intersection of wireless co
 mmunications and machine learning. He is one of the core developers and ma
 intainers of the Sionna open-source link-level simulator. Before joining N
 VIDIA\, he received his PhD in Electrical Engineering and Information Tech
 nology from the University of Stuttgart\, Germany. His main research inter
 ests are machine learning for wireless communications and channel coding. 
 His work has been recognized with several awards\, including the VDE ITG D
 issertationspreis 2022\, the IEEE SPS Young Author Best Paper Award 2019\,
  and third prize in the Nokia Bell Labs Prize 2019.&lt;/span&gt;&lt;/p&gt;\n&lt;p class=&quot;
 MsoNormal&quot; style=&quot;margin-bottom: 0cm\; text-align: justify\;&quot;&gt;&amp;nbsp\;&lt;/p&gt;
END:VEVENT
END:VCALENDAR