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IEEE International Conference on Acoustics Speech and Signal Processing

Robust joint beamforming and artificial noise design for amplify-and-forward multi-antenna relay systems

Lijian Zhang, Liang Jin, Wenyu Luo, Yanqun Tang, Dingjiu Yu

Published Apr 1, 2015• 4 citations
Publisher

Abstract

In this paper, we address physical layer security for amplify-and-forward (AF) multi-antenna relay systems in the presence of multiple eavesdroppers. A robust joint design of cooperative beamforming (CB) and artificial noise (AN) is proposed with imperfect channel state information (CSI) of both the destination and the eavesdroppers. We aim to maximize the worst-case secrecy rate subject to the sum power and the per-antenna power constraints at the relay. Such joint design problem is non-convex. By utilizing the semidefinite relaxation (SDR) technique, S-procedure and the successive convex approximation (SCA) algorithm, the original non-convex optimization problem is recast into a series of semidefinite programs (SDPs) which can be efficiently solved using interior-methods. Simulation results are presented to verify the effectiveness of the proposed design.

DOI
10.1109/icassp.2015.7178267

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This letter studies the secure cooperative transmission for an amplify-and-forward (AF) relay network in the presence of multiple multi-antenna eavesdroppers. Since the perfect channel state information (CSI) of the eavesdroppers are not available, we propose a robust joint distributed beamforming and artificial noise scheme to maximize the worst-case secrecy rate of the network, under the total power constraint of all the relay nodes. With the semidefinite relaxation (SDR) technique, the design can be solved by a one-dimension search which involves a sequence of semidefinite programming (SDP). Simulation results demonstrate the validity of the proposed strategy.
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In this letter, a joint design of cooperative beamforming (CB) and artificial noise (AN) is proposed for two-way amplify-and-forward (AF) relay networks to improve the security of the date exchange. Based on secrecy sum rate maximization (SSRM) criterion, such joint design problem under individual relay power constraints is mathematically hard due to the non-convex objective function. By utilizing the semidefinite relaxation (SDR) technique and successive convex approximation (SCA) algorithm, we efficiently develop a stationary point for the original SSRM design problem. Proof is also given to show that SDR is always tight and yields a rank-one solution. Simulations are presented to validate the efficiency and merits of our proposed joint CB and AN design in enhancing the secrecy sum rate.
This paper investigates the physical-layer security issue of an amplify-and-forward (AF) relay network. We propose a joint cooperative beamforming (CB) and cooperative jamming (CJ) design that is robust to the imperfect channel state information (CSI) of the multiple multiantenna eavesdroppers. The objective is the worst-case secrecy rate maximization (WCSRM). Based on the inner convex approximation and semidefinite relaxation (SDR) technique, the original nonconvex problem is transformed into a sequence of approximate convex problems, which can be solved conveniently. The proposed robust design guarantees to converge to a Karush-Kuhn-Tucker (KKT) solution and is efficient in computational complexity. Furthermore, we prove that SDR always has a rank-1 solution, which identifies that SDR is tight. Simulations demonstrate the validity of the proposed strategy.
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In this paper, we study the secrecy transmission in multi-antenna relay networks with multiple eavesdroppers. The relay employs the amplify-and-forward relaying protocol and simultaneously sends the artificial noise to interfere the eavesdroppers. It is assumed that only imperfect channel state information on the main and eavesdropping channels is available at the relay. We exploit the robust beam forming and jamming to maximize the worst-case secrecy rate under a total relay power budget. Because of the infinitely nonconvex constraints, the problem is difficult to solve. Therefore, we approximate the problem into several tractable semi definite programs by semi definite relaxation, S-procedure, and the successive convex approximation techniques. Simulation results show the effectiveness of the proposed scheme.