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IEEE Transactions on Vehicular Technology

Robust Joint Beamforming and Jamming for Secure AF Networks: Low-Complexity Design

Chao Wang, Hui‐Ming Wang

Published Jul 2, 2014• 70 citations
Publisher

Abstract

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.

DOI
10.1109/tvt.2014.2334640

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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.
This paper studies the design of cooperative beamforming (CB) and cooperative jamming (CJ) for the physical layer security of an amplify-and-forward (AF) relay network in the presence of multiple multi-antenna eavesdroppers. The secrecy rate maximization (SRM) problem of such a network is to maximize the difference of two concave functions, a problem which is non-convex and has no efficient solution. Based on the inner convex approximation (ICA) and semidefinite relaxation (SDR) techniques, we propose two novel low-complexity schemes to design CB and CJ for SRM in the AF network. In the first strategy, relay nodes adopt the CB only to secure transmission. Based on ICA, this design guarantees convergence to a Karush-Kuhn-Tucker (KKT) solution of the SDR of the original problem. In the second strategy, the optimal joint CB and CJ design is studied and the proposed joint design can guarantee convergence to a KKT solution of the original problem. Moreover, in the second strategy, we prove that SDR always has a rank-1 solution for the SRM problem. Simulation results show the superiority of the proposed schemes.
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.
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.
In this paper, we study robust joint beamforming and cooperative jamming (CJ) in a secure decode-and-forward (DF) relay system in the presence of multiple eavesdroppers, in which a multi-antenna DF relay employs transmit beamforming to help the source deliver information to the destination and simultaneously generates Gaussian artificial noise to confuse these eavesdroppers. We assume that all the channel state information (CSI) is imperfectly known at the relay subject to norm-bounded CSI errors. Our objective is to maximize the achievable secrecy rate at the destination by jointly optimizing the transmit beamforming vector of information signals and the covariance matrix of jamming signals at the relay subject to its total transmit power constraint. Although this problem is non-convex and in general difficult to be solved, we obtain its optimal solution via the technique of semi-definite relaxation (SDR) together with a one-dimensional (1-D) search. Specifically, we prove that the SDR is tight for the problem of our interest. Finally, numerical results are provided to validate our proposed scheme.
This paper studies cooperative secure transmission in wireless relay networks, where a source sends a confidential message to a legitimate destination through a set of amplify-and-forward (AF) relays in the presence of multiple eavesdroppers. To prevent the eavesdroppers from retrieving the message, we assume that the relays employ a joint cooperative beamforming (CB) and artificial noise (AN) strategy. Under both the total and individual relay power constraints, we propose an optimal joint CB-AN design based on secrecy rate maximization (SRM). We treat the SRM problem by a combination of two-level optimization and semidefinite relaxation (SDR). For the latter, we prove that SDR always has a rank-one solution for the SRM problem - which identifies that SDR is optimal. Simulation results are presented to show the efficacy of the proposed joint CB-AN design.
This paper is concerned with an optimization problem in a two-hop relay wiretap channel, wherein multiple multi-antenna relays collaboratively amplify and forward (AF) information from a single-antenna source to a single-antenna destination, and at the same time emit artificial noise (AN) to improve physical-layer information security in the presence of multiple multi-antenna eavesdroppers (or Eves). More specifically, the problem is to simultaneously optimize the AF matrices and AN covariances for secrecy rate maximization, with robustness against imperfect channel state information of Eves via a worst-case robust formulation. Such a problem is nonconvex, and we propose a polynomial-time optimization solution based on a two-level optimization approach and semidefinite relaxation (SDR). In particular, while SDR is generally an approximation technique, we prove that SDR is optimal in the specific context here. This desirable result is obtained by careful reformulation and Karush-Kuhn-Tucker optimality analysis, where, rather interestingly, AN is found to be instrumental in providing guarantee of SDR optimality. Simulation results are provided, and the results show that the proposed joint AF-AN solution can attain considerably higher achievable secrecy rates than some existing suboptimal designs.