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IEEE International Conference on Acoustics Speech and Signal Processing

Joint transmit beamforming and artificial noise design for QoS discrimination inwireless downlink

Wei-Cheng Liao, Tsung‐Hui Chang, Wing‐Kin Ma, Chong‐Yung Chi

Published Jan 1, 2010• 34 citations
Publisher

Abstract

This paper considers a downlink wireless system where a multiple-antenna transmitter (Alice) aims to discriminate the reception performances between a legitimate receiver (Bob) and a set of unauthorized receivers (Eves). To this end, there has been great interest in the use of artificial noise (AN) together with transmit beamforming in order to effectively interfere Eves' reception. However, most of the existing works do not optimize the AN but simply allocate it in the left null space of the Alice-to-Bob channel. In the paper, we propose to jointly optimize the beamforming vector and the AN covariance matrix by minimizing the total transmit power subject to a target signal-to-interference-plus-noise ratio (SINR) constraint on Bob and limited SINR constraints on all Eves. While the considered beamforming problem is not convex and may be difficult to solve in general, it can be effectively handled by a convex approximation method called semidefinite program (SDP) relaxation. In addition to showing how SDP relaxation can be applied to this problem, we prove using the KKT optimality that SDP relaxation provides a global optimum solution of the proposed beamforming problem when Alice has perfect information of the channel from Alice to Bob. Simulation results are presented to demonstrate the effectiveness of the proposed beamforming method.

DOI
10.1109/icassp.2010.5496291

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This paper considers a downlink wireless system where a multiple-antenna transmitter (Alice) aims to discriminate the reception performances between a legitimate receiver (Bob) and a set of unauthorized receivers (Eves). To this end, there has been great interest in the use of artificial noise (AN) together with transmit beamforming in order to effectively interfere Eves' reception. However, most of the existing works do not optimize the AN but simply allocate it in the left null space of the Alice-to-Bob channel. In the paper, we propose to jointly optimize the beamforming vector and the AN covariance matrix by minimizing the total transmit power subject to a target signal-to-interference-plus-noise ratio (SINR) constraint on Bob and limited SINR constraints on all Eves. While the considered beamforming problem is not convex and may be difficult to solve in general, it can be effectively handled by a convex approximation method called semidefinite program (SDP) relaxation. In addition to showing how SDP relaxation can be applied to this problem, we prove using the KKT optimality that SDP relaxation provides a global optimum solution of the proposed beamforming problem when Alice has perfect information of the channel from Alice to Bob. Simulation results are presented to demonstrate the effectiveness of the proposed beamforming method.
Consider the multi-input single-output multi-eavesdroppers (MISOMEs) wireless communication system. Our goal is to design an artificial noise (AN)-aided secure transmit strategy to safeguard this system from the perspective of quality-of-service (QoS). Specifically, we propose two design formulas: (1) total power minimization design under signal-to-interference-plus-noise ratio (SINR) constraints on receiver and eavesdroppers; (2) receiver's SINR maximization design under constraints of transmitted total power and eavesdroppers' SINRs. The proposed design problems jointly optimizing the information covariance and AN covariance are solved by semidefinite program (SDP) optimization approach. Through exploring the Karush-Kuhn-Tucker conditions of SDP problems, it is proved that transmit beamforming is the optimal strategy for confidential information transmission in the two designs. Finally, simulation results demonstrate that the proposed AN-aided approach in the two designs provides the best performance compared to isotropic AN and no-AN approach.
This paper studies secure wireless transmission from a multi-antenna transmitter to a single-antenna intended receiver overheard by multiple eavesdroppers with considering the imperfect channel state information (CSI) of wiretap channel.To enhance security of communication link, the artificial noise (AN) is generated at transmitter.We first design the robust joint optimal beamforming of secret signal and AN to minimize transmit power with constraints of security quality of service (QoS), i.e., minimum allowable signal-to-interference-and-noise ratio (SINR) at receiver and maximum tolerable SINR at eavesdroppers.The formulated design problem is shown to be nonconvex and we transfer it into linear matrix inequalities (LMIs).The semidefinite relaxation (SDR) technique is used and the approximated method is proved to solve the original problem exactly.To verify the robustness and tightness of proposed beamforming, we also provide a method to calculate the worst-case SINR at eavesdroppers for a designed transmit scheme using semidefinite programming (SDP).Additionally, the secrecy rate maximization is explored for fixed total transmit power.To tackle the nonconvexity of original formulation, we develop an iterative approach employing sequential parametric convex approximation (SPCA).The simulation results illustrate that the proposed robust transmit schemes can effectively improve the transmit performance.
Secure transmission techniques have been receiving growing attention in recent years, as a viable, powerful alternative to blocking eavesdropping attempts in an open wireless medium. This paper proposes a secret transmit beamforming approach using a quality-of-service (QoS)-based perspective. Specifically, we establish design formulations that: i) constrain the maximum allowable signal-to-interference-and-noise ratios (SINRs) of the eavesdroppers, and that ii) provide the intended receiver with a satisfactory SINR through either a guaranteed SINR constraint or SINR maximization. The proposed designs incorporate a relatively new idea called artificial noise (AN), where a suitable amount of AN is added in the transmitted signal to confuse the eavesdroppers. Our designs advocate joint optimization of the transmit weights and AN spatial distribution in accordance with the channel state information (CSI) of the intended receiver and eavesdroppers. Our formulated design problems are shown to be NP-hard in general. We deal with this difficulty by using semidefinite relaxation (SDR), an approximation technique based on convex optimization. Interestingly, we prove that SDR can exactly solve the design problems for a practically representative class of problem instances; e.g., when the intended receiver's instantaneous CSI is known. Extensions to the colluding-eavesdropper scenario and the multi-intended-receiver scenario are also examined. Extensive simulation results illustrate that the proposed AN-aided designs can yield significant power savings or SINR enhancement compared to some other methods.
This paper studies the secure communication between a multiple-antenna transmitter (Alice) and a single-antenna destination (Bob) in the presence of more than one eavesdroppers (Eves). The optimal beamforming weights and the covariance matrix of artificial noise (AN) are obtained by minimizing the total transmission power of Alice, subject to a target secrecy rate constraint for Bob. We propose a two-level optimization method, where the inner-level optimization is solved by an interesting semidefinite relaxation method of W. C. Liao et al., and the outer-level optimization is solved by the golden section method. Our algorithm converges quite fast. Some properties of the optimal solution are also provided to illustrate the features of this problem.
In this work, a robust artificial noise (AN) aided transmit method is proposed for a multicast multiple-input single-output (MISO) system in the presence of multiple single-antenna eavesdroppers. With the imperfect covariance-based channel state information (CSI), we aim to minimize the transmit power at the transmitter under the multicast secrecy rate constraint and the maximum transmit power constraint. The resulting optimization problem involves the joint optimization of the beamforming vector and AN covariance matrix. After using the semidefinite relaxation (SDR) technique, we derive the exact reformulation of the original optimization through the Lagrange duality. Then this non-convex problem is transformed into a one-variable optimization problem, which can be handled by solving a series of semidefinite programs (SDPs). Simulation results demonstrate the effectiveness of the proposed robust transmit method.
This paper studies secure communication from a multi-antenna transmitter to a single-antenna receiver in the presence of multiple multi-antenna eavesdroppers, considering constraints of security quality of service (QoS), i.e., minimum allowable signal-to-interference-and-noise ratio (SINR) at receiver and maximum tolerable SINR at eavesdroppers. The robust joint optimal beamforming (RJOBF) of secret signal and artificial noise (AN) is designed to minimize transmit power while estimation errors of channel state information (CSI) for wiretap channels are taken into consideration. The formulated design problem is shown to be nonconvex and we transfer it into linear matrix inequalities (LMIs) along with semidefinite relaxation (SDR) technique. The simulation results illustrate that our proposed RJOBF is efficient for power saving in security communication.