Scholar
Sami Muhaidat
Google Scholar ID: UDXNqUgAAAAJ
Professor, Khalifa University; Adjunct Professor, Carleton University
Citations & Impact
Citations
7,374
H-index
42
i10-index
145
Publications
20
Co-authors
40
list available
Contact
Publications
Resume (English only)
Academic Achievements
- Made seminal contributions in the areas of low power wireless networks, cognitive radio networks, MIMO, cooperative communication networks, optical communications, wireless power transfer, hardware impairments, mmWave, and non-orthogonal multiple access (NOMA) for 5G and beyond (5GB) networks. Currently, he is an Area Editor of the IEEE Transactions on Communications and Lead Guest Editor of the IEEE OJ-COMS “Large-Scale Wireless Powered Networks with Backscatter Communications” special issue. He served as a Senior Editor and Editor of the IEEE Communications Letters, an Editor of the IEEE Transactions on Communications, and an Associate Editor of the IEEE Transactions on Vehicular Technology.
Research Experience
- From 2008-2012, he was an Assistant Professor in the School of Engineering Science, Simon Fraser University, BC, Canada. He is currently a Professor and Theme Leader in the Center for Cyber-Physical Systems, Khalifa University, UAE, and also an Adjunct Professor with the Department of Systems and Computer Engineering, Carleton University.
Education
- Received the Ph.D. degree in Electrical and Computer Engineering from the University of Waterloo, Canada in 2006. From 2007 to 2008, he was an NSERC postdoctoral fellow in the Department of Electrical and Computer Engineering, University of Toronto, Canada.
Background
- Research Interests: Cognitive Radio Networks, Optical wireless communications, Multiple-input-multiple-output (MIMO) and Spatial modulation, Non-orthogonal multiple access (NOMA), Reconfigurable intelligent surfaces, Backscatter communications, Physical Layer Security, Machine learning for wireless communications, Unmanned aerial vehicle communications. Professional field: Communication theory with particular emphasis on the physical layer aspects of wireless communication networks; Machine learning and their applications in the field of wireless networks.
