Department of Electrical and Computer Engineering, Khalifa University
Opportunistic Ambient Backscatter Communications in RF-Powered Cognitive Radio Networks
The exponential growth in data traffic, due to the emergence of the Internet of Things (IoT) and the increasing number of connected devices, poses unique challenging and stringent requirements for 5G wireless networks and beyond. These requirements include, but not limited to, high spectral and energy efficiency, low latency, and massive connectivity. A particularly interesting proposal was the development of cognitive radio (CR), which has been shown to be efficient in maximizing the utilization of the spectrum due to its inherent spectrum sensing (SS) capability. Recently, the integration of RF energy harvesting with CR networks has led to the development of a new communication paradigm, known as RF-powered CR networks. In these networks, a CR transmitter harvests RF energy when a primary user (PU) is present, which is then used for data transmission during the idle period of the PU. This protocol is referred to it as harvest-then-transmit (HTT). A major challenge, however, is the reduction in the throughput of the secondary network when the harvested energy is low and/or when the data transmission time is short. More recently, Ambient Backscatter Communications (ABC) has emerged as a new communication paradigm with low power and cost requirements. In a CR network, a CR transmitter can send data to a CR receiver by backscattering the PU signal when it is present. Clearly, the performance of ABC-based CR networks greatly depends on the availability of PU signal, which represents a key challenge, particularly, during the long idle periods. In this talk, we discuss the recent developments of ABC in the context of cognitive radio. We further discuss a new opportunistic hybrid ABC-HTT model for CR networks, coined as ABC-HTT-based CR networks. Finally, we analyze and evaluate the energy efficiency performance of the new scheme considering sensing errors under different scenarios.
Sami Muhaidat received the Ph.D. degree in Electrical and Computer Engineering from the University of Waterloo, Waterloo, Ontario, in 2006. From 2007 to 2008, he was an NSERC postdoctoral fellow in the Department of Electrical and Computer Engineering, University of Toronto, Canada. From 2008-2012, he was an Assistant Professor in the School of Engineering Science, Simon Fraser University, BC, Canada. He is currently an Associate Professor at Khalifa University, anda Visiting Reader (Associate Professor) in the Faculty of Engineering, University of Surrey, UK. Sami's research focuses on wireless communications, physical-layer security, IoT with emphasis on battery-less devices, and machine learning. Sami is currently an Area Editor for IEEE Transactions on Communications. He served as a Senior Editor for IEEE Communications Letters, an Editor for IEEE Transactions on Communications, and an Associate Editor for IEEE Transactions on Vehicular Technology. He is also a member of Mohammed Bin Rashid Academy of scientists.