Abstract

Visible light communication (VLC) has emerged as a disruptive form of wireless communication. VLC systems can achieve high data rates, low latency, and high security. However, the performance of VLC in different scenarios significantly depends on several practical considerations such as transmitter nonlinearities, random blockages, random receiver orientation, and user mobility.

A promising approach to address such issues and deliver superior performance is the use of machine learning for VLC design. In this talk, we will introduce the application of machine learning techniques for several VLC systems, discuss contemporary results and provide an outlook on future research challenges.

About Speaker 

Dr. Himal A. Suraweera (Senior Member, IEEE) is a senior lecturer in the Department of Electrical and, Electronic Engineering, University of Peradeniya, Sri Lanka. He is in the editorial boards of IEEE Transactions on Communications and IEEE Open Journal of the Communications Society. Previously he has served as an editor for IEEE Communications Letters, IEEE Transactions on Wireless Communications and IEEE Transactions on Green Communications and Networking.

He was a recipient/co-recipient of the IEEE ComSoC AP Outstanding Young Researcher Award in 2011 and the IEEE ComSoc Leonard G. Abraham Prize in 2017. He has been involved as a co-chair, Signal Processing for Communications Symposium of IEEE GLOBECOM 2015, and track chair of Full- Duplex Communications Track, Symposium on Selected Areas in Communications of IEEE ICC 2022. His research interests are in the areas of wireless communications, signal processing for communications and communication theory, in particular, cooperative communications systems, full- duplex wireless techniques, energy harvesting communications, massive MIMO systems, cognitive radio and machine learning for communications.