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PRODID:IEEE vTools.Events//EN
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DTSTART:20240310T030000
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DTSTART:20231105T010000
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DTSTAMP:20231113T140826Z
UID:E2CF2AC6-8B2A-483A-B4F0-62F8491245D4
DTSTART;TZID=America/New_York:20231107T100000
DTEND;TZID=America/New_York:20231107T110000
DESCRIPTION:As a well recognized disruptive technology\, visible light comm
 unication (VLC) delivers high data rates and improved security to be activ
 ely considered for many new indoor and outdoor applications in future wire
 less communication systems. Over the years\, VLC system modeling\, analysi
 s and implementation have been an active research field enriched with mult
 iple seminal developments reported in the literature. More recently\, data
 -driven machine learning techniques have emerged to revolutionize conventi
 onal communication system design and optimization. In this talk\, we will 
 discuss how such machine learning techniques can be effectively applied fo
 r the design and optimization of VLC systems including examples taken from
  spatial modulation in VLC\, simultaneous lightwave and power transfer (SL
 IPT) and intelligent reflective surface aided VLC systems.\n\nSpeaker(s): 
 Himal A. Suraweera\, \n\nVirtual: https://events.vtools.ieee.org/m/37678
 4
LOCATION:Virtual: https://events.vtools.ieee.org/m/376784
ORGANIZER:Toronto_Chapter@comsoc.org
SEQUENCE:14
SUMMARY:Realizing Visible Light Communication for Future Wireless Systems: 
 A Machine Learning Approach
URL;VALUE=URI:https://events.vtools.ieee.org/m/376784
X-ALT-DESC:Description: &lt;br /&gt;&lt;p&gt;As a well recognized disruptive technology
 \, visible light communication (VLC) delivers high data rates and improved
  security to be actively considered for many new indoor and outdoor applic
 ations in future wireless communication systems. Over the years\, VLC syst
 em modeling\, analysis and implementation have been an active research fie
 ld enriched with multiple seminal&amp;nbsp\;developments reported in the liter
 ature. More recently\, data-driven machine learning techniques have emerge
 d to revolutionize conventional communication system design and optimizati
 on. In this talk\, we will discuss how such machine learning&amp;nbsp\;techniq
 ues can be effectively applied for the design and optimization of VLC syst
 ems including examples taken from spatial modulation in VLC\, simultaneous
  lightwave and power transfer (SLIPT) and intelligent reflective surface a
 ided VLC systems.&amp;nbsp\; &amp;nbsp\;&lt;/p&gt;
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