VIRTUAL DISTINGUISHED LECTURE “ARTIFICIAL INTELLIGENCE (AI) FOR MASSIVE INTERNET OF THINGS (MIOT)”- DR. ARUMUGAM NALLANATHAN
“Artificial Intelligence (AI) for Massive Internet of Things (mIoT)”.
Dr. Arumugam Nallanathan on April 20th 17 Hs USA EDT
(22 Hs London /18 Hs Arg Bra Chi Uru / 16Hs Ecu Per Col Mex / 15 HS Costa Rica).
Arumugam Nallanathan, FIET, FIEEE, Professor of Wireless Communications, Head of Communication Systems Research (CSR) Group, School of Electronic Engineering and Computer Science, Faculty of Science and Engineering, Queen Mary University of London, Mile End Road, London, E1 4NS, United Kingdom, Web: http://www.eecs.qmul.ac.uk/~nalla/
SHORT-BIO:
Arumugam Nallanathan is Professor of Wireless Communications and Head of the Communication Systems Research (CSR) group in the School of Electronic Engineering and Computer Science at Queen Mary University of London since September 2017. He was with the Department of Informatics at King’s College London from December 2007 to August 2017, where he was Professor of Wireless Communications from April 2013 to August 2017 and a Visiting Professor from September 2017. He was an Assistant Professor in the Department of Electrical and Computer Engineering, National University of Singapore from August 2000 to December 2007.
His research interests include Artificial Intelligence for Wireless Systems, 5G and beyond Wireless Networks, Internet of Things (IoT) and Molecular Communications. He published nearly 500 technical papers (including more than 200 top IEEE journal papers) in scientific journals and international conferences. He is a co-recipient of the Best Paper Awards presented at the IEEE International Conference on Communications 2016 (ICC’2016), IEEE Global Communications Conference 2017 (GLOBECOM’2017) and IEEE Vehicular Technology Conference 2017 (VTC’2017). He is an Editor for IEEE Transactions on Communications and a Senior Editor for IEEE Wireless Communications Letters. He was an Editor for IEEE Transactions on Wireless Communications (2006-2011), IEEE Transactions on Vehicular Technology (2006-2017) and IEEE Signal Processing Letters. He served as the Chair for the Signal Processing and Communication Electronics Technical Committee of IEEE Communications Society and Technical Program Chair and member of Technical Program Committees in numerous IEEE conferences. He received the IEEE Communications Society SPCE outstanding service award 2012 and IEEE Communications Society RCC outstanding service award 2014. He has been selected as a Web of Science (ISI) Highly Cited Researcher in 2016. He is an IEEE Fellow and IEEE Distinguished Lecturer.
ABSTRACT: Cellular-based networks are expected to offer connectivity for massive Internet of Things (mIoT) systems. However, their Random Access CHannel (RACH) procedure suffers from unreliability, due to the collision from the simultaneous massive access. Despite that this collision problem has been treated in existing RACH schemes, these schemes usually organize IoT devices’ transmission and re-transmission along with fixed parameters, thus can hardly adapt to time-varying traffic patterns. Without adaptation, the RACH procedure easily suffers from high access delay, high energy consumption, or even access unavailability. In this talk, how to optimize the RACH procedure in real-time by maximizing a long-term hybrid multi-objective function, which consists of the number of access success devices, the average energy consumption, and the average access delay will be presented.
DATE AND TIME
LOCATION
HOSTS
REGISTRATION
- Date: 20 Apr 2021
- Time: 05:00 PM to 06:00 PM
- All times are America/New_York
- Add Event to Calendar
Registered attendes, will be mailed with the WEBINAR link 24 hours before the event.
- Montevideo
- MONTEVIDEO
- Uruguay
- Uruguay Section Chapter, COM19
- Co-sponsored by IEEE Uruguay
- Starts 07 April 2021 06:00 AM
- Ends 20 April 2021 02:00 AM
- All times are America/New_York
- No Admission Charge
Agenda
REGISTERED ATEENDES WILL BE MAILED THE CONNECTION LINK 24 HOURS BEFORE THE EVENT:
REGISTRATION LINK: https://events.vtools.ieee.org/event/register/269122
EVENT: https://events.vtools.ieee.org/m/269122