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X-WR-CALNAME:IEEE Toronto Section
X-ORIGINAL-URL:https://www.ieeetoronto.ca
X-WR-CALDESC:Events for IEEE Toronto Section
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DTSTART:20220101T000000
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DTSTART;TZID=UTC:20231107T100000
DTEND;TZID=UTC:20231107T110000
DTSTAMP:20260506T233619
CREATED:20231003T233329Z
LAST-MODIFIED:20231107T093117Z
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SUMMARY:Realizing Visible Light Communication for Future Wireless Systems: A Machine Learning Approach
DESCRIPTION: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 applications in future wireless communication systems. Over the years\, VLC system modeling\, analysis and implementation have been an active research field enriched with multiple seminal developments reported in the literature. More recently\, data-driven machine learning techniques have emerged to revolutionize conventional communication system design and optimization. In this talk\, we will discuss how such machine learning techniques can be effectively applied for the design and optimization of VLC systems including examples taken from spatial modulation in VLC\, simultaneous lightwave and power transfer (SLIPT) and intelligent reflective surface aided VLC systems.  Speaker(s): Himal A. Suraweera\,   Virtual: https://events.vtools.ieee.org/m/376784
URL:https://www.ieeetoronto.ca/event/realizing-visible-light-communication-for-future-wireless-systems-a-machine-learning-approach/
LOCATION:Virtual: https://events.vtools.ieee.org/m/376784
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