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IEEE International Conference on Communication Technology (ICCT)

Artificial Noise assisted Secure Transmission using Novel Beamforming Scheme based on Statistical CSI

Xiaoyu Zhang, Yutao Lu, Hua Fu, Kang Zheng

Published Oct 20, 2023• 1 citation
Publisher

Abstract

We propose a secure transmission scheme that employs artificial noise (AN) to enhance information security. This scheme uses a novel beam design method based on a specific type of statistical Channel State Information (CSI) known as the channel statistical covariance matrix. The base station can acquire this matrix through prior measurements. By performing eigenvalue decomposition on this matrix, we can extract valuable engineering insights from its eigenvalue and eigenvectors, which represent beam domain information within the channel. Leveraging this information, we further design an optimization problem to minimize the eavesdropper's Signal-to-Noise-Plus-Interference Ratio (SINR) through joint optimization of beam selection and power allocation. Eventually, an iterative algorithm is proposed to solve this optimization problem. Numerical results reveal favorable secrecy performance of our beamforming scheme under CDL channel models.

DOI
10.1109/icct59356.2023.10419814

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We propose a secure transmission scheme that employs artificial noise (AN) to enhance information security. This scheme uses a novel beam design method based on a specific type of statistical Channel State Information (CSI) known as the channel statistical covariance matrix. The base station can acquire this matrix through prior measurements. By performing eigenvalue decomposition on this matrix, we can extract valuable engineering insights from its eigenvalue and eigenvectors, which represent beam domain information within the channel. Leveraging this information, we further design an optimization problem to minimize the eavesdropper's Signal-to-Noise-Plus-Interference Ratio (SINR) through joint optimization of beam selection and power allocation. Eventually, an iterative algorithm is proposed to solve this optimization problem. Numerical results reveal favorable secrecy performance of our beamforming scheme under CDL channel models.
For the single-cell massive multiple-input multiple-output (MIMO) downlink transmission, we investigate an artificial noise (AN) assisted secure transmission strategy where the base station has only access to statistical channel state information (CSI) of the legitimate user terminals and the eavesdropper. By maximizing a lower bound of the ergodic secrecy sum rate, we figure out the eigenvectors of the optimal secrecy signal and AN transmit covariance matrices in the closed-form. Notably, such a solution reveals that it is more favorable to transmit both the secrecy signals and the AN in the beam domain, by which we translate the original problem into a simpler power allocation problem in the beam domain. Building on the approaches of sequential optimization and the deterministic equivalent, we further propose an iterative algorithm for power allocation with guaranteed convergence to a local optimum. Numerical results show the superior performance of the proposed approach compared with the traditional one without AN.
Statistical channel state information (CSI) can be obtained by pre-measuring the user’s channel, unlike instantaneous CSI which is only available after the user has accessed the network. Hence, the statistical CSI can be used to achieve confidential transmission and protect the access process of legitimate users. In this paper, we propose a beam selection scheme based on statistical CSI for discrete Fourier transform beamforming. Assuming that the statistical CSIs of the legitimate user and the eavesdropper are available at the base station, we adopt artificial noise (AN) in transmission and minimize the signal-to-noise-plus-interference ratio of the eavesdropper. The beam selection scheme can be converted into a semidefinite program problem. The performance of the system has been tested in both line-of-sight and non-line-of-sight scenarios using a 5G clustered delay line channel model. The simulation results show that, by transmitting AN, the performance of eavesdropper rapidly degrades when the eavesdropper moves away from the legitimate user.
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 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.
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.
Secure communication with noisy feedback is studied in this correspondence. Unlike the majority of previous research efforts where the eavesdropper's channel state information (CSI)-either instantaneous or statistical CSI, is known by the legitimate users, a joint feedback and artificial noise scheme without any eavesdropper's CSI is proposed. The proposed scheme lets the source and the legitimate destination alternatively transmit private messages and degrade the eavesdropper's channel quality in all transmission phases. An insightful discovery is that if the transmit power is lager than a certain threshold, a positive secrecy capacity can be achieved, which overcomes the problem that the secrecy cannot be achieved when the legitimate user's CSI is worse than the eavesdropper's. The secrecy capacity maximization problem is investigated by adaptive power allocation for the private signals and the artificial noise where a near optimal solution of the power of artificial noise is obtained under the high SNR situation. Finally, the numerical results verify the theoretical analysis and illustrate the secrecy performance of the proposed scheme.