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VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
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TZID:Asia/Kolkata
BEGIN:STANDARD
DTSTART:19451014T230000
TZOFFSETFROM:+0630
TZOFFSETTO:+0530
TZNAME:IST
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BEGIN:VEVENT
DTSTAMP:20260327T095230Z
UID:2960C72D-DD93-4C4B-BFCF-D332D0C62EBE
DTSTART;TZID=Asia/Kolkata:20260323T140000
DTEND;TZID=Asia/Kolkata:20260323T150000
DESCRIPTION:The transition from 5G to 6G is expected to bring artificial in
 telligence into the core of wireless communication systems. This talk high
 lights how AI can improve key aspects of communication such as channel est
 imation\, modulation\, and resource management\, leading to better perform
 ance and lower overhead. Beyond individual components\, AI enables smarter
  networks that can automatically adjust to changing environments and user 
 needs. The presentation also discusses the idea of AI-based foundation mod
 els for wireless channels\, which can learn and generate realistic communi
 cation scenarios. Overall\, this approach aims to make future 6G systems m
 ore intelligent\, efficient\, and adaptable.\n\nSpeaker(s): Dr. Ashok Kuma
 r Reddy C\, \n\nBldg: LHC CR-001\, Indian Institute of Technology Tirupati
 \, Tirupati\, Andhra Pradesh\, India\, 517619
LOCATION:Bldg: LHC CR-001\, Indian Institute of Technology Tirupati\, Tirup
 ati\, Andhra Pradesh\, India\, 517619
ORGANIZER:ee22d001@iittp.ac.in
SEQUENCE:21
SUMMARY:AI-Native 6G: Recent Results and 6G Roadmap
URL;VALUE=URI:https://events.vtools.ieee.org/m/550247
X-ALT-DESC:Description: <br /><p>The transition from 5G to 6G is expected t
 o bring artificial intelligence into the core of wireless communication sy
 stems. This talk highlights how AI can improve key aspects of communicatio
 n such as channel estimation\, modulation\, and resource management\, lead
 ing to better performance and lower overhead. Beyond individual components
 \, AI enables smarter networks that can automatically adjust to changing e
 nvironments and user needs. The presentation also discusses the idea of AI
 -based foundation models for wireless channels\, which can learn and gener
 ate realistic communication scenarios. Overall\, this approach aims to mak
 e future 6G systems more intelligent\, efficient\, and adaptable.</p>
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