IEEE Communications Letters · 2019 · 581 citations · 18 references
EngineeringElectrical EngineeringMathematicsAntennasOptimizationWireless CommunicationsAntenna DesignMimo AntennasPhysical Layer SecuritySmart AntennasWireless Network SecurityAlternating MinimizationCovarianceInformation-theoretic Secrecy CapacityPhase ShiftsSecrecy Rate OptimizationSecure Transmission DesignSmart Antenna SystemsTransmission Optimization
The study aims to maximize the secrecy rate of IRS‑assisted multi‑antenna systems under transmit power and unit‑modulus constraints. An alternating algorithm is proposed that obtains closed‑form transmit covariance and semi‑closed‑form IRS phase shifts. The algorithm converges theoretically and simulation results demonstrate a performance advantage over existing designs.
We investigate transmission optimization for intelligent reflecting surface (IRS) assisted multi-antenna systems from the physical-layer security perspective. The design goal is to maximize the system secrecy rate subject to the source transmit power constraint and the unit modulus constraints imposed on phase shifts at the IRS. To solve this complicated non-convex problem, we develop an efficient alternating algorithm where the solutions to the transmit covariance of the source and the phase shift matrix of the IRS are achieved in closed form and semi-closed form, respectively. The convergence of the proposed algorithm is guaranteed theoretically. Simulation results validate the performance advantage of the proposed optimized design.
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Semidefinite Relaxation of Quadratic Optimization Problems
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On Nonlinear Fractional Programming
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