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Artificial-noise aided secure transmission over visible light communication system under coexistent passive and active eavesdroppers

Ge Shi, Yong Li, Wei Cheng, Xiang Gao, Limeng Dong

Published Feb 4, 2022• 5 citations
Publisher

Abstract

In this paper, secure transmission over multiple-input single-output visible light communication system under coexistent passive and active eavesdroppers (Eves) is studied. To enhance the achievable secrecy rate of this system given statistical channel state information (CSI) error model for the passive Eves-related channels, a robust artificial-noise (AN) based transmit strategy is proposed and a secrecy rate maximization problem subject to secrecy-outage-probability constraint, sum power constraint, and peak amplitude constraint is formulated. To solve this non-convex problem, a conservative approximation is presented to replace the probabilistic constraint and unbounded CSI error with worst-case secrecy constraints and spherically-bounded CSI errors, respectively. Then, semi-definite relaxation, S -procedure, and a Golden search-based algorithm are proposed to solve the approximated problem with fast convergence and low complexity. Simulation results show that the proposed method outperforms the other AN-aided and non-AN method for the coexistent active and passive Eves case, especially when the power budget is high.

DOI
10.1364/oe.448860

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In this paper, secure transmission over multiple-input single-output visible light communication system under coexistent passive and active eavesdroppers (Eves) is studied. To enhance the achievable secrecy rate of this system given statistical channel state information (CSI) error model for the passive Eves-related channels, a robust artificial-noise (AN) based transmit strategy is proposed and a secrecy rate maximization problem subject to secrecy-outage-probability constraint, sum power constraint, and peak amplitude constraint is formulated. To solve this non-convex problem, a conservative approximation is presented to replace the probabilistic constraint and unbounded CSI error with worst-case secrecy constraints and spherically-bounded CSI errors, respectively. Then, semi-definite relaxation, S -procedure, and a Golden search-based algorithm are proposed to solve the approximated problem with fast convergence and low complexity. Simulation results show that the proposed method outperforms the other AN-aided and non-AN method for the coexistent active and passive Eves case, especially when the power budget is high.
In this paper, we consider improving the secure performance of multiple-input single-output visible light communication channel in the presence of multiple eavesdroppers with multiple photodiodes. Our goal is to design an optimal artificial-noise (AN) aided transmission strategy to maximize the achievable secrecy rate subject to both sum power constraint and peak amplitude constraint. We consider a joint optimization of the transmit covariance and AN covariance for the non-convex secrecy rate maximization (SRM) problem. In order to solve it, the SRM problem is transformed into a series of single-variable semidefinite programming (SDP) problems without losing any optimality, and a one-dimensional search based algorithm is proposed to handle the converted problem, with polynomial complexity. By exploiting Karush-Kuhn-Tucker conditions of the problem, beamforming is found to be optimal for the confidential information transmission. Simulation results show the superior performance of the proposed AN-aided method compared with two other AN-aided methods and no AN-aided method.
This paper studies the design of energy-efficient artificial noise (AN) schemes in the context of physical layer security in visible light communications (VLC). Two different transmission schemes termed selective AN-aided single-input single-output (SISO) and AN-aided multiple-input single-output (MISO) are examined and compared in terms of secrecy energy efficiency (SEE). In the former, the closest LED luminaire to the legitimate user (Bob) is the information-bearing signal’s transmitter. At the same time, the rest of the luminaries act as jammers transmitting AN to degrade the channels of eavesdroppers (Eves). In the latter, the information-bearing signal and AN are combined and transmitted by all luminaries. When Eves’ CSI is unknown, an indirect design to improve the SEE is formulated by maximizing Bob’s channel’s energy efficiency. A low-complexity design based on the zero-forcing criterion is also proposed. In the case of known Eves’ CSI, we study the design that maximizes the minimum SEE among those corresponding to all eavesdroppers. At their respective optimal SEEs, simulation results reveal that when Eves’ CSI is unknown, the selective AN-aided SISO transmission can archive twice as good SEE as the AN-aided MISO does. In contrast, when Eves’ CSI is known, the AN-aided MISO outperforms by 30%.
Consider an MISO channel overheard by multiple eavesdroppers. Our goal is to design an artificial noise (AN)-aided transmit strategy, such that the achievable secrecy rate is maximized subject to the sum power constraint. AN-aided secure transmission has recently been found to be a promising approach for blocking eavesdropping attempts. In many existing studies, the confidential information transmit covariance and the AN covariance are not simultaneously optimized. In particular, for design convenience, it is common to prefix the AN covariance as a specific kind of spatially isotropic covariance. This paper considers joint optimization of the transmit and AN covariances for secrecy rate maximization (SRM), with a design flexibility that the AN can take any spatial pattern. Hence, the proposed design has potential in jamming the eavesdroppers more effectively, based upon the channel state information (CSI). We derive an optimization approach to the SRM problem through both analysis and convex conic optimization machinery. We show that the SRM problem can be recast as a single-variable optimization problem, and that resultant problem can be efficiently handled by solving a sequence of semidefinite programs. Our framework deals with a general setup of multiple multi-antenna eavesdroppers, and can cater for additional constraints arising from specific application scenarios, such as interference temperature constraints in interference networks. We also generalize the framework to an imperfect CSI case where a worst-case robust SRM formulation is considered. A suboptimal but safe solution to the outage-constrained robust SRM design is also investigated. Simulation results show that the proposed AN-aided SRM design yields significant secrecy rate gains over an optimal no-AN design and the isotropic AN design, especially when there are more eavesdroppers.
In this letter, considering the simultaneous wireless information and power transfer scheme, we study the robust artificial noise (AN)-aided secure transmission design in multiple-input-single-output channels where the channel uncertainties are modeled by worst-case model. Our objective is to maximize the worst-case secrecy rate with respect to both the worst-case channel uncertainties and the worst-case eavesdropper among multiple eavesdroppers, under the transmit power constraint and the worst-case energy harvesting constraint. The optimal solution to the problem can be found by two-dimensional (2-D) search. Since the 2-D search algorithm has high computational complexity, we propose to neglect the correlation of the channel uncertainties from the transmitter to the information-decoding receiver and reformulate the problem as a sequence of convex semidefinite programming (SDP) which is solved efficiently by SDP based one-dimensional line search method. It is shown through computer simulations that the proposed robust AN-aided secure transmission schemes have significant performance gain over the non-robust AN-aided secure transmission scheme and the robust secure transmission scheme without the aid of AN.
In this paper, the physical-layer secrecy problem is investigated for the indoor multiple-input single-output (MISO) visible light communication systems. First, when the channel state information (CSI) of eavesdroppers is perfect, two kinds of optimal secure beamformers are, respectively, designed to minimize the transmit power and to maximize the secrecy rate. Moreover, it is shown that the secrecy rate maximization problem can be decomposed into a sequence of convex feasibility problems, which can be efficiently solved by using interior point methods. Second, when the CSI of eavesdroppers is imperfect, an ellipsoidal region model is applied to characterize the CSI uncertainty. This model leads to an infinite number of complicated constraints for the design of robust secure beamformers. By using theS\mathcal {S}S-lemma and semidefinite relaxation, this nonconvex problem is transformed into the convex semidefinite program. Finally, numerical results demonstrate the optimality and robustness of the proposed methods.
In this paper, we consider a multiuser multiple-input multiple-output (MIMO) downlink communication system with simultaneous wireless information and power transfer (SWIPT). In particular, we focus on a realistic and efficient multi-receiver multi-eavesdropper MIMO SWIPT system, in which the channel state information (CSI) of each legitimate receiver and energy receiver (i.e., potential eavesdropper) is partially known to the transmitter. Based on this, we propose a robust artificial noise (AN)-aided secure transmission scheme for the system, where the channel uncertainties are modeled by the worst-case model. In the proposed scheme, we aim to maximize the worst-case achievable secrecy rate under the transmit power constraint and the energy harvesting (EH) constraint, by jointly optimizing the transmit precoding matrix and the AN covariance matrix. We utilize the S-Procedure and Taylor series approximation to transform the non-convex problem. Then, we apply the interior point method to tackle the transformed convex problem, obtaining the approximate optimal matrices and the corresponding maximum worst-case secrecy rate. Simulation results show that our proposed scheme achieves significant performance improvements in terms of convergence and the worst-case achievable secrecy rate.