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Robust artificial noise assisted secure transceiver optimization in AF relay networks with multiple source-destination pairs

机译:在具有多个源-目标对的AF中继网络中,可靠的人工噪声辅助安全收发器优化

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We consider an amplify-and-forward (AF) relay network with multiple source-destination pairs in the presence of an eavesdropper. This paper studies the robust artificial noise (AN) assisted joint transceiver optimization for secure communication with imperfect channel state information (CSI) of legitimate users and no CSI regarding the eavesdropper. The goal is to design the linear precoding matrix of the relay and the linear equalizer of each destination, such that the transmit power for the information-bearing signals and forwarded background noises at the relay can be minimized subject to the quality of service (QoS) constraints at the destinations. The remainder of the constrained total power is used to generate the AN for jamming the eavesdropper. Although such a power minimization problem is nonconvex, we recast it into two semidefinite programming (SDP) subproblems which can be solved using interior-point methods. Then this problem can be solved with the alternating iterative optimization algorithm. Simulations demonstrate that the proposed algorithm can significantly reduce the sensitivity to imperfect CSI, while degrading the eavesdropper's capability of intercepting.
机译:我们考虑在存在窃听者的情况下具有多个源-目的地对的放大转发(AF)中继网络。本文研究了鲁棒的人工噪声(AN)辅助联合收发器优化,用于使用合法用户的不完善信道状态信息(CSI)进行安全通信,而没有关于窃听者的CSI。目的是设计中继器的线性预编码矩阵和每个目标的线性均衡器,以便可以根据服务质量(QoS)最小化中继器上的信息承载信号的传输功率和转发的背景噪声目的地的限制。约束总功率的其余部分用于生成AN,以干扰窃听者。尽管这种功率最小化问题不是凸性的,但我们将其重铸为两个半定性编程(SDP)子问题,可以使用内点方法解决。然后可以使用交替迭代优化算法解决该问题。仿真表明,该算法可以显着降低对不完善CSI的敏感性,同时降低窃听者的监听能力。

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