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2019.5.26--Energy Harvesting Cognitive Non-Orthogonal Multiple Access:Optimal Resource Allocation
May 16, 2019


Energy Harvesting Cognitive Non-Orthogonal Multiple Access:   Optimal Resource Allocation


Prof.   Hai Jiang


2019-05-16 09:30:00


1012 meeting room in the New Technology   Building of North Campus

Lecturer    Profile

Hai Jiang received the B.Sc. and M.Sc. degrees in electronics   engineering from Peking University, Beijing, China, in 1995 and 1998,   respectively, and the Ph.D. degree in electrical engineering from the   University of Waterloo, Waterloo, Ontario, Canada, in 2006. Since July 2007,   he has been a faculty member with the University of Alberta, Edmonton,   Alberta, Canada, where he is currently a Professor at the Department of   Electrical and Computer Engineering. Dr. Jiang received an Alberta Ingenuity   New Faculty Award in 2008, a Best Paper Award from the IEEE Global   Communications Conference (GLOBECOM) in 2008, a Faculty of Engineering   Research Award from the Faculty of Engineering, University of Alberta, in   2015, and a Best Paper Award from the Green Communications & Computing   Technical Committee, IEEE Communications Society, in 2018. His research   interests include radio resource management, cognitive radio networking, and   cooperative communications.

Lecture    Abstract

 In   this talk, we will discuss a cognitive radio system, in which a secondary   transmitter harvests energy from a primary transmitter's RF signal. The   secondary transmitter, which provides decode-and-forward relaying service for   the primary system, transmits its own data by using downlink non-orthogonal   multiple access (NOMA). A time-switching protocol is used by the secondary   transmitter to harvest energy and decode the primary transmitter's   information. Our objective is to achieve maximal secondary throughput, by   optimally selecting the time portion used for energy harvesting and the   secondary transmitter's power allocation in NOMA transmission. Two   optimization problems are formulated, in which the secondary receiver   performs or does not perform successive interference cancellation (SIC),   respectively. Although the two problems are nonconvex, we devise a method to   transform the problems into equivalent problems under difference cases. Then   we theoretically prove that the objective functions of the equivalent   problems are quasiconcave, based on which we develop two-level bisection   search algorithms to solve the equivalent problems. Interestingly, we show   that performing SIC at the secondary receiver does not always guarantee a   higher secondary throughput than the case without performing SIC.


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