In this paper, we consider a backscatter communication (BackCom) based cognitive network that consists of one primary transmitter, one primary receiver,multiple secondary transmitters (STs), and one secondary receiver (SR). Each SToperates in the BackCom or energy harvesting model. Our goal is to jointly optimize the energy harvesting and backscatter time, the transmit power of the primary transmitter, and the power reflection coefficient of each ST to maximize the sum throughput of all the STs under a nonlinear energy harvestingmodel while satisfyingmultiple constraints, i.e., the energy causality of each ST, the Quality of Service of the primary transmitter, etc. The formulated problem is nonconvex due to the coupled variables and hard to solve. In order to address this problem, we decouple partial coupled variables by using the properties of the objective function and constructing auxiliary variables, and the remaining coupled variables are decoupled via successive convex approximation (SCA). On this basis, a SCA based iterative algorithm is developed to solve the formulated problem. Simulation results are provided to support our work.
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