Title :
Robust Artificial Noise Aided Transmit Method for Multicast MISO Wiretap Channels with Imperfect Covariance-Based CSI
Author :
Lijian Zhang ; Liang Jin ; Wenyu Luo ; Zhou Zhong ; Dingjiu Yu
Author_Institution :
Zhengzhou Inf. Sci. & Technol. Inst., Zhengzhou, China
Abstract :
In this work, a robust artificial noise (AN) aided transmit method is proposed for a multicast multiple-input single-output (MISO) system in the presence of multiple single-antenna eavesdroppers. With the imperfect covariance-based channel state information (CSI), we aim to minimize the transmit power at the transmitter under the multicast secrecy rate constraint and the maximum transmit power constraint. The resulting optimization problem involves the joint optimization of the beamforming vector and AN covariance matrix. After using the semidefinite relaxation (SDR) technique, we derive the exact reformulation of the original optimization through the Lagrange duality. Then this non-convex problem is transformed into a one-variable optimization problem, which can be handled by solving a series of semidefinite programs (SDPs). Simulation results demonstrate the effectiveness of the proposed robust transmit method.
Keywords :
concave programming; covariance matrices; multicast communication; radio transmitters; wireless channels; AN covariance matrix; Lagrange duality; MISO system; artificial noise; beamforming vector; channel state information; imperfect covariance-based CSI; maximum transmit power constraint; multicast MISO wiretap channels; multicast secrecy rate constraint; multiple-input single-output system; nonconvex problem; one-variable optimization problem; radio transmitter; robust AN aided transmit method; semidefinite relaxation technique; single-antenna eavesdroppers; Array signal processing; Covariance matrices; Noise; Optimization; Robustness; Simulation; Uncertainty;
Conference_Titel :
Vehicular Technology Conference (VTC Spring), 2015 IEEE 81st
Conference_Location :
Glasgow
DOI :
10.1109/VTCSpring.2015.7146063