Considering that an illegitimate user wants to eavesdrop on the messages which are broadcasted from the base station to two legitimate users, we study the robust artificial-noise-aided optimal beamforming scheme where imperfect channel state information(CSI) is assumed. Our aim is to maximize the sum of the achievable secrecy rate, subject to the sum of the power. We propose to apply S-procedure to reformulate it and employ an alternating optimization(AO) algorithm to solve the problem. Simulation results show that our proposed scheme is superior to the non-robust one.
Considering that an illegitimate user wants to eavesdrop on the messages which are broadcasted from the base station to two legitimate users, we study the robust artificial-noise-aided optimal beamforming scheme where imperfect channel state information(CSI) is assumed. Our aim is to maximize the sum of the achievable secrecy rate, subject to the sum of the power. We propose to apply S-procedure to reformulate it and employ an alternating optimization(AO) algorithm to solve the problem. Simulation results show that our proposed scheme is superior to the non-robust one.
In this paper, we propose a novel layered physical layer security model, which is the extension of the traditional physical layer security to the domain of multiple-layer information security. It has a hierarchical information security structure that every transmitted message has a security level, while every user has a security clearance. Users can only decode the messages with security levels lower than or equal to their clearance, otherwise they will be deemed as eavesdroppers. Based on the framework of the layered information security and assuming perfect channel state information of all users, an artificial-noise-aided optimal beamforming scheme is proposed to minimize the total transmit power at the base station, while satisfying the minimum secrecy rate requirements of all secret messages. Due to the intrinsical complexity of the formulated nonconvex problem, a safe and convex reformulation based on the first-order Taylor series expansion method is proposed to generate a tractable approximation. A successive convex approximation-based algorithm is then proposed, which solves a series of second-order cone problems with convergence to the stationary point of the original problem. We also consider the imperfect channel state information case, and then propose a worst-case robust design to overcome the influence of channel uncertainties. Semi-definite relaxation method and S-procedure are utilized to get a computationally efficient lower bound of the intractable power minimization problem. Moreover, we investigate the application of the suboptimal zero-forcing-based beamforming scheme in the system to tradeoff the achievable performance and the computational complexity. Simulation results are provided to demonstrate the effectiveness of our proposed schemes.
Physical layer security has recently emerged as a promising approach to provide secure wireless communications. Physical layer security technology is the key means to achieve security and communication integration. The built-in security mechanism based on the characteristics of wireless channel provides a feasible idea for the realization of “one secret at a time”. It has important application prospects in integrity protection of service data, Internet of things (IoT) lightweight encryption and blockchain wireless security technology. In this paper, we consider the scenario of a unicast multiuser multiple-input single-output (MISO) downlink system in the presence of multiple single-antenna passive eavesdroppers. Instead of assuming perfect channel state information (CSI), we investigate the artificial noise (AN)-aided robust transmit beamforming scheme with imperfect CSI on legitimate receivers and no CSI regarding eavesdroppers at the transmitter. Under the fixed total transmit power, the information symbol and the AN are transmitted concurrently. We aim to guarantee each legitimate receiver's signal-to-interference-and-noise ratio(SINR) outage probability below a preset level with minimum power. Hence, as much power as possible can be allocated to AN to confuse the eavesdroppers. In order to reduce the negative impact on the legitimate receivers, the AN is transmitted in the null space of the estimated legitimate channels. To deal with this nonconvex optimization problem, a rank relaxed formulation is obtained by employing semidefinite relaxation (SDR). Then we propose two approaches by using Bernstein-type inequality and S-procedure, respectively, to transform the probabilistic constraints into deterministic constraints. The optimization problem is reformulated as a convex semidefinite program (SDP). Simulation results show that the proposed approaches have better performances than the non-robust approach.
In this letter, we develop a novel layered physical layer security model to secure multiple messages simultaneously. It maintains a hierarchical security structure, in which each message transmitted from the base station has a security level, and each user in the network has a security clearance correspondingly. Focusing on the basic two-layer unicast system, we propose an artificial-noise-aided optimal beamforming scheme to maximize the higher level information security performance while adhering to the low-level information secrecy rate constraint. Due to the nonconvexity of the problem formulated, a successive convex approximation-based algorithm is proposed to earn a safe convex approximation of the original. Afterward, a low-complexity zero-forcing beamforming scheme is proposed to achieve high efficiency by reducing the computational complexity. Simulation results validate the superiority of our schemes on the promotion of the overall secrecy performance.
This paper studies masked beamforming schemes for secure communication in broadcast multiple-input multiple-output (MIMO) systems with a passive multiple-antenna eavesdropper. Assuming no information about the eavesdropper is available at the transmitter, we aim to maximize the transmit power of the artificial noise while meeting mean square error (MSE) constraints at the legitimate receivers and the total power constraint at the transmitter. Based on imperfect channel state information (CSI) of the legitimate receivers at the transmitter, we present a worst-case robust masked beamforming algorithm. By exploiting alternating iterative optimization, the proposed algorithm recasts the non-convex optimization problem as two semidefinite program (SDP) based subproblems, which are solvable with interior-point methods. Simulation results are provided to illustrate the secrecy performance of the proposed algorithm.
In this paper, we investigate the physical layer security of a full-duplex base station (BS)-aided system in the worst case, where an uplink transmitter (UT) and a downlink receiver (DR) are equipped with a single antenna, while a powerful eavesdropper is equipped with multiple antennas. For securing the confidentiality of signals transmitted from the BS and UT, an artificial noise (AN)-aided secrecy beamforming scheme is proposed, which is robust to the realistic imperfect state information of both the eavesdropping channel and the residual self-interference channel. Our objective function is that of maximizing the worst-case sum secrecy rate achieved by the BS and UT, through jointly optimizing the beamforming vector of the confidential signals and the transmit covariance matrix of the AN. However, the resulting optimization problem is non-convex and non-linear. In order to efficiently obtain the solution, we transform the non-convex problem into a sequence of convex problems by adopting the block coordinate descent algorithm. We invoke a linear matrix inequality for finding its Karush-Kuhn-Tucker (KKT) solution. In order to evaluate the achievable performance, the worst-case secrecy rate is analytically derived. Furthermore, we construct another secrecy transmission scheme using the projection matrix theory for performance comparison. Our simulation results show that the proposed robust secrecy transmission scheme achieves substantial secrecy performance gains, which verifies the efficiency of the proposed method.
In this paper, we consider max-min fairness for a downlink two-user multi-input single-output (MISO) system with imperfect channel state information available at transmitter (CSIT) taking into account the total power constraint and the physical layer security. Considering the worst-case channel uncertainty for a potential eavesdropper (PE), we study the robust secure beamforming algorithm design which maximizes the minimum achieved worst-case secrecy rate among single-antenna legitimate users. In contrast to existing schemes adopted in the literatures, we propose a rather unorthodox rate splitting (RS) scheme which advocates the dual use of a common message serving both as a desired message and artificial noise (AN) for legitimate users and the PE, respectively. The algorithm design is formulated as a non-convex optimization problem which is generally intractable. As a compromise approach, we apply the successive convex approximation (SCA) method which facilitates the design of a low-complexity suboptimal iterative algorithm. In each iteration, a rank-constrained semi-definite program (SDP) is solved optimally by SDP relaxation (SDR). Simulation results demonstrate that our proposed robust secure beamforming scheme in the MISO-RS secure transmission system outperforms that of the non-robust counterpart. Moreover, our results also unveil that the proposed RS scheme can achieve a superior performance compared to the existing non-orthogonal multiple access (NOMA) schemes and the traditional scheme.