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IEEE Signal Processing Letters

Cooperative Secure Beamforming for AF Relay Networks With Multiple Eavesdroppers

Ye Yang, Qiang Li, Wing‐Kin Ma, Jianhua Ge, P.C. Ching

Published Nov 20, 2012• 178 citations
Publisher

Abstract

This letter studies cooperative secure beamforming for amplify-and-forward (AF) relay networks in the presence of multiple eavesdroppers. Under both total and individual relay power constraints, we propose two schemes, namely secrecy rate maximization (SRM) beamforming and null-space beamforming. In the first scheme, our design problem is based on SRM. Using a suboptimal, but convex, technique-semidefinite relaxation (SDR), we show that this problem can be handled by performing a one-dimensional search which involves solving a sequence of semidefinite programs (SDPs). To reduce the complexity, in the second scheme, we instead maximize the information rate at the destination while completely eliminating the information leakage to all eavesdroppers. We prove that this problem can be exactly solved by SDR with one SDP only. Simulation results demonstrate the performance gains of the two proposed designs.

DOI
10.1109/lsp.2012.2227313

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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.
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 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.
We study the transmit design at relay nodes for secure amplify-and-forward (AF) networks. Two joint cooperative relaying and jamming schemes, namely Secrecy Rate Maximization Scheme and Null-Space Jamming Scheme, are proposed. In the first scheme, optimal relaying weight vector and optimal covariance matrix associated with the artificial noise (AN) are obtained, which involves doing a one-dimensional search and solving a sequence of semidefinite programs(SDPs). In the second scheme, which is suboptimal but computationally much cheaper, AN is designed to decrease the rate at the eavesdropper while the relaying weight vector is determined to increase the rate at the destination. In addition, Power Allocation based on secrecy rate maximization provides a balance between these two goals. Numerical results show that the proposed Secrecy Rate Maximization Scheme outperforms the existing cooperative relaying without jamming scheme. Especially, when the power is large enough, the secrecy rate achieved by the proposed schemes approaches the maximal achievable rate for the no-eavesdropper case.
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.