IEEE Access · 2018 · 23 citations · 37 references
EngineeringComputer EngineeringElectrical EngineeringInformation TheoryOptimizationWireless CommunicationsCognitive RadioConvex OptimizationInformation-theoretic SecurityNetwork Information TheoryPhysical Layer SecurityPower OptimizationBernstein InequalityChannel State InformationCognitive Radio NetworksEnergy HarvestingOutage ProbabilitySemidefinite ProgrammingSemidefinite Programming RelaxationSemidefinite Relaxation
This paper studies the secure transmit design for a downlink multiple-input-single-output cognitive radio network (CRN) with a practical energy harvesting (EH) model. Due to the open architecture of a CRN, the confidential information intended for the secondary receiver is prone to be eavesdropped by external eavesdroppers (Eves). Specifically, considering imperfect channel state information, our aim is to jointly design the transmit beamforming vector and the power splitting ratio, such that the outage-constrained secrecy rate is maximized under the constraints of total power consumption, secrecy rate outage probability, EH and quality of service requirements. The original problem is not convex and intractable in general, in order to tackle this non-convexity issue, we utilize semidefinite relaxation and Bernstein-type inequality to transform the outage constraints into a deterministic form. We show that the optimal solution can be obtained by alternately optimizing two convex subproblems. Also, we prove that the optimal solution of the relaxed problem will always be rank one. Furthermore, we consider a large deviation inequality (LDI)-based approach to obtain a sub-optimal solution, which can significantly reduce the computational complexity. Finally, simulation results have been provided to demonstrate the performance of our proposed designs.
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Natural Sciences, Electrical Engineering, Digital Communication +16