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IEEE Military Communications Conference (MILCOM)

Robust Beamforming and Jamming for Secure AF Relay Networks with Multiple Eavesdroppers

Cong Zhang, Hui Gao, Haijing Liu, Tiejun Lv

Published Oct 1, 2014• 13 citations
Publisher

Abstract

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.

DOI
10.1109/milcom.2014.89

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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.
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.
We address a robust beamforming design and power allocation problem for a one-way multi-antenna relay network, where the multi-antenna source implements communication with the multi-antenna destination via a decode-and-forward (DF) relay in the presence of the multiple single-antenna eavesdroppers. The eavesdroppers can only overhear the information flowed from the relay to the destination in the second hop. We aim to maximize the worst-case secrecy rate in the condition that the global channel state information (CSI) is imperfect. To this end, we propose the joint beamforming and power allocation design for the worst-case secrecy rate maximization. However, our proposed design constitutes a non-convex problem, which involves an infinite number of constraints because of the imperfect CSI. To make the problem more tractable, we approximate the problem into several tractablesemidefinite programs by semidefinite relaxation, successive convex approximation, and S-procedure techniques, and we propose an iterative algorithm to solve the problem. Furthermore, we show that the proposed algorithm is also applicable for the case the Gaussian wiretap model, where only the eavesdroppers' CSI is imperfect. Simulation results validate the effectiveness of the proposed algorithm.
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.
In this paper, we compute worst case secrecy rates in amplify-and-forward (AF) relay beamforming with cooperative jamming (CJ) in the presence of imperfect channel state information (CSI). A source-destination pair aided by M relays is considered. Number of eavesdroppers J can be more than the number of relays. Out of the M relays, k1relays (1 ≤ k1≤ M) act as data relays and the remaining k2= M - k1relays act as jamming relays. Data relays aid the communication by relaying data in AF mode, and jamming relays cooperate by transmitting jamming signals (artificial noise). The jamming signals are created such that they degrade the eavesdroppers' channels but do not significantly affect the intended receiver's channel, thereby improving secrecy rate. Imperfection in the CSI is modeled using a norm-bounded error model. We solve for the optimum (k1, k2) and the weights of data relays and jamming relays that maximize the secrecy rate subject to a total relay power constraint. We relax the rank-one constraint on the complex semi-definite data relays and jamming relays weight matrices and reformulate the optimization problem into a form that can be solved using convex semi-definite programming. Numerical results on the secrecy rate that illustrate the effect of cooperative jamming, imperfect CSI, and number of eavesdroppers are presented.