For simultaneous wireless information and power transfer (SWIPT), secure communication is an important issue. In this letter, we consider a wireless multiple-input-single-output secure communication system with SWIPT overheard by multiple multi-antenna eavesdroppers. In the system, a transmitter employs artificial noise (AN)-aided transmission and a legitimate receiver employs power splitting (PS) to harvest energy. Our objective is to jointly design AN-aided transmission and PS scheme which maximizes achievable secrecy rate under transmit power constraint and energy harvesting constraint. We propose to include an equality constraint to convert the constraint on information rate from transmitter to eavesdroppers into linear matrix inequalities. Replacing the equality constraint with a convex constraint and a concave constraint, we propose to employ constrained concave convex procedure based algorithm to find a local optimum of the problem. Simulation results demonstrate that the proposed joint optimization of AN-aided transmission and PS scheme outperforms the non-AN-aided one.
For simultaneous wireless information and power transfer (SWIPT), secure communication is an important issue. In this letter, we consider a wireless multiple-input-single-output secure communication system with SWIPT overheard by multiple multi-antenna eavesdroppers. In the system, a transmitter employs artificial noise (AN)-aided transmission and a legitimate receiver employs power splitting (PS) to harvest energy. Our objective is to jointly design AN-aided transmission and PS scheme which maximizes achievable secrecy rate under transmit power constraint and energy harvesting constraint. We propose to include an equality constraint to convert the constraint on information rate from transmitter to eavesdroppers into linear matrix inequalities. Replacing the equality constraint with a convex constraint and a concave constraint, we propose to employ constrained concave convex procedure based algorithm to find a local optimum of the problem. Simulation results demonstrate that the proposed joint optimization of AN-aided transmission and PS scheme outperforms the non-AN-aided one.
This letter investigates a multiple-input single-output secrecy channel, where the legitimate user and the eavesdroppers employ a power splitting scheme for information decoding and energy harvesting (EH), simultaneously. An artificial noise is embedded to the information bearing signal to interfere the eavesdroppers and to harvest power by all receivers (i.e., legitimate user and eavesdroppers). We consider the robust secrecy rate maximization problem subject to the transmit power and the EH constraints by incorporating the norm-bounded channel uncertainty. This robust optimization problem is not convex, and thus, it can be reformulated as a convex one along with matrix transformations and convex conic optimization techniques, which is iteratively solved based on constrained concave-convex procedure-based algorithm. Finally, numerical results are provided to validate our proposed algorithm.
Considering simultaneous wireless information and power transfer (SWIPT), we investigate cooperative-jamming (CJ) aided robust secure transmission design in multiple-input-single-output channels, where a cooperative jammer introduces jamming interferences and assists a source to supply wireless power for both an energy receiver and a legitimate destination. The destination employs a power splitting (PS) scheme to split the received signals for both information decoding and energy harvesting (EH). Compared with conventional transmission without SWIPT, the transmission with SWIPT should satisfy additional worst-case EH constraints. Furthermore, the PS scheme introduces an additional multiplicative optimization variable, i.e., the PS factor. Our objective is to maximize worst-case secrecy rate under transmit power constraints and worst-case EH constraints. We propose to decouple the problem into three optimization problems and employ alternating optimization algorithm to obtain the locally optimal solution. For the optimization of transmit covariance matrices and PS factor, we propose to employ the S-procedure and its extension to reformulate it as a convex semidefinite programming. It is shown through the simulation results that our proposed CJ aided robust secure transmission scheme outperforms the robust direct transmission scheme without CJ and the CJ aided non-robust scheme.
In this paper, we investigate the secure transmission in multiple-input multiple-output (MIMO) communication systems with simultaneous wireless information and power transfer (SWIPT), where the energy receivers (ERs) may eavesdrop the confidential information send to the desired receiver (DR). By taking into account both artificial noise (AN) and power splitting (PS), we aim to maximize the secrecy rate at the DR by jointly designing the precoding matrix, AN covariance matrix and PS ratio at the desired receiver, under the transmit power constraint and the energy harvesting (EH) constraints at all the receivers. To solve the formulated non-convex problem, we propose an alternating optimization (AO) algorithm through a judicious reformulation, wherein the problem is handled by solving a series of convex problems in an alternating method. Finally, numerical results are provided to validate our proposed algorithm.
In this paper, we study the secure transmission scheme in multiple-input multiple-output (MIMO) communication systems with simultaneous wireless information and power transfer (SWIPT), in which both power splitting (PS) receiver and artificial noise (AN) are taken into account. We aim to maximize the achievable secrecy rate at the desired receiver by jointly designing precoding matrix, AN covariance matrix and PS ratio at the desired receiver, under the total transmit power constraint and the minimum energy harvesting constraints at all the receivers. The formulated optimization problem is nonconvex and hard to tackle. Then, by transforming this problem into a canonical DC (difference of convex function) programming, we propose an iterative method to solve this problem, and analyze the convergence of the proposed algorithm. Simulation results are provided to show the efficiency of our proposed scheme.
This paper considers transmit covariance matrix design for secrecy rate maximization problem in a multiple-input single-output (MISO) multicasting simultaneous wireless information and power transfer (SWIPT) system. In order to enhance the performance of the system, artificial noise (AN) is added to the transmit signal in the design for the following purposes: to reduce the received signal-to-noise ratio (SNR) at the eavesdroppers and increase the harvested energy. We assume that all the channel-state-information (CSI) is perfectly known at the transmitter and all legitimate users are capable of simultaneously receiving information and harvesting energy. In addition, all the eavesdroppers are passive and they can harvest energy only when they are not intercepting or eavesdropping the messages intended for the legitimate users. The original secrecy rate maximization problem is not convex in terms of transmit and artificial covariance matrices as well as the power splitting (PS) ratio. In order to circumvent this non-convexity issue, we exploit the \emph{Charnes-Cooper} Transformation and semidefinite relaxation (SDR) to convert this original problem into a convex one. However, this convex problem does not always yield the rank-one transmit and AN covariance matrices to obtain the solution of the original problem. Therefore, we analyze the optimal conditions and utilize a Gaussian randomization (GR) method to construct the rank-one solutions from the non-rank one results. Simulation results have been provided to demonstrate the performance of the proposed transmit covariance matrices design for MISO multicasting SWIPT system.
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.