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Robust Artificial Noise Aided Transmit Method for Multicast MISO Wiretap Channels with Imperfect Covariance-Based CSI

机译:具有不完全基于协方差的CSI的多播Miso丝网通道的强大人工噪声辅助发送方法

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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.
机译:在这项工作中,提出了一种稳健的人工噪声(AN)辅助发送方法,用于多播多输入单输出(MISO)系统,在存在多个单天线窃听器的情况下。利用基于协方差的不完全协方差的信道状态信息(CSI),我们的目的是在多播保密率约束下最小化发射机处的发射功率和最大发射功率约束。得到的优化问题涉及波束形成矢量和协方差矩阵的联合优化。在使用Semidefinite放松(SDR)技术后,我们通过拉格朗日二元衍出原始优化的精确重新制定。然后将该非凸面问题转换为一个可变优化问题,可以通过求解一系列半纤维精细程序(SDP)来处理。仿真结果证明了所提出的鲁棒传递方法的有效性。

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