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IEEE Transactions on Vehicular Technology

Robust AN-Aided Secure Precoding for an AF MIMO Untrusted Relay System

Quanzhong Li, Liang Yang, Qi Zhang, Jiayin Qin

Published Sep 4, 2017• 20 citations
Publisher

Abstract

Robust artificial noise (AN) aided secure precoding for an amplify-and-forward multiple-input multiple-output untrusted relay system is studied, where the relay is untrusted and willing to help forwarding multiple data streams from the source to destination. We consider that the available channel state information is imperfect and modeled by the worst case model. Our objective is to maximize the worst case secrecy rate under the robust transmit power constraints at the source and relay, by jointly designing the signal and AN precoding matrices at the source and the precoding matrix at the relay. The robust secure precoding problem is nonconvex and hard to solve. To overcome this difficulty, we propose the weighted minimum mean square error based method, where the signdefiniteness lemma is used to eliminate the channel uncertainties and an effective iterative optimization algorithm is developed. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.

DOI
10.1109/tvt.2017.2748605

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Robust artificial noise (AN) aided secure precoding for an amplify-and-forward multiple-input multiple-output untrusted relay system is studied, where the relay is untrusted and willing to help forwarding multiple data streams from the source to destination. We consider that the available channel state information is imperfect and modeled by the worst case model. Our objective is to maximize the worst case secrecy rate under the robust transmit power constraints at the source and relay, by jointly designing the signal and AN precoding matrices at the source and the precoding matrix at the relay. The robust secure precoding problem is nonconvex and hard to solve. To overcome this difficulty, we propose the weighted minimum mean square error based method, where the signdefiniteness lemma is used to eliminate the channel uncertainties and an effective iterative optimization algorithm is developed. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.
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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.
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We consider a secrecy dual-hop amplify-and-forward (AF) untrusted relay network, where the relay is willing to forward the signal to the destination while acting as a potential eavesdropper. Assuming that all these nodes are equipped with multiple antennas, we propose a joint destination aided cooperative jamming and precoding at both the source and the relay scheme, with the objective to maximize the worst case secrecy rate. The formulated problem is highly non-convex due to the maximization of the difference of several logarithmic determinant (log-det) functions in the CSI uncertainty region. To handle this challenge, we propose to linearize these log-det terms. After linearization, we tackle the CSI uncertainty based on epigraph reformulation and the sign-definiteness lemma. Finally, an alternating optimization (AO) algorithm is proposed to solve the reformulated problem. Numerical results are provided to demonstrate the performance of the proposed scheme.
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