In this paper, we study the multiple-input multiple-output (MIMO) wiretap channel performing simultaneous wireless information and power transfer (SWIPT), where there are a multiple-antenna base station (BS), a multiple-antenna information decoding (ID) user, and a multiple-antenna energy harvesting (EH) user. The messages intended to the ID user need to be kept confidential to the EH user. The channels between BS and users are modeled as fading channels with different spatial correlations and line-of-sight (LoS) components. We assume that only statistical channel state information (CSI) is available at the BS. Our objective is to design the optimal transmit covariance matrix at the BS for maximizing the ergodic secrecy rate subject to the BS power constraint and the harvested energy requirement for the EH user. To this end, we present an approximation for the ergodic secrecy rate by using large dimensional random matrix theory and the method of Taylor series expansion. Based on this, an iterative algorithm is proposed to find the transmit covariance matrix. Simulation results are provided to verify the accuracy of the approximation and the performance of the design.
In this paper, we study the multiple-input multiple-output (MIMO) wiretap channel performing simultaneous wireless information and power transfer (SWIPT), where there are a multiple-antenna base station (BS), a multiple-antenna information decoding (ID) user, and a multiple-antenna energy harvesting (EH) user. The messages intended to the ID user need to be kept confidential to the EH user. The channels between BS and users are modeled as fading channels with different spatial correlations and line-of-sight (LoS) components. We assume that only statistical channel state information (CSI) is available at the BS. Our objective is to design the optimal transmit covariance matrix at the BS for maximizing the ergodic secrecy rate subject to the BS power constraint and the harvested energy requirement for the EH user. To this end, we present an approximation for the ergodic secrecy rate by using large dimensional random matrix theory and the method of Taylor series expansion. Based on this, an iterative algorithm is proposed to find the transmit covariance matrix. Simulation results are provided to verify the accuracy of the approximation and the performance of the design.
In this letter, we consider a multiple-input-multiple-output (MIMO) downlink system with simultaneous wireless information and power transfer (SWIPT), where the information sent to the desired receiver (DR) may be wiretapped by the malicious energy harvesting (EH) receivers (potential eavesdroppers). Assuming the channel state information (CSI) of the EH receivers is not perfectly known at the transmitter, we aim to maximize the worst-case secrecy rate by jointly designing the precoding matrix, AN covariance matrix and power splsplitting ratio, under the constraints of total transmit power and harvested energyitting ratio, under the constraints of total transmit power and harvested energy at receivers. The formulated problem is non-convex and semi-infinite, which is hard to tackle. To solve it, we first deal with the non-convexity caused by CSI errors with the aid of the S-Procedure, and then employ the Taylor series approximation techniques to transfer the nonconvex problem into a convex optimization problem. Based on that, we propose an iterative algorithm with proved convergence to solve the original problem. Simulation results are finconvex optimization problem. Based on that, we propose an iterative algorithmally provided to show the effectiveness of our proposed robust transmit design.
Owing to the wireless signal power received by the energy harvesting (EH) node is generally higher than that of the information decoding (ID) node in simultaneous wireless information and power transfer (SWIPT) system, the confidential information becomes vulnerable to be wiretapped. Motivated, in this paper, we aim at realizing secure communications for two-user MIMO interference channel with SWIPT. Unfortunately, the formulated secrecy rate maximization problem is non-convex with respect to the covariance matrices of two transmitters, thus an alternative algorithm is proposed to solve the nonconvex optimization problem. Firstly, the orthogonal-projection-based optimization algorithm is performed to completely suppress the interference to ID receiver, then by applying the Taylor series expansion, the covariance matrix of information transmitter is optimized based on the dual optimization. Finally, numerical experiments are conducted to validate the security performance of the proposed algorithm.
This letter studies transmit optimization in three-node multiple-input-multiple-output wiretap channels with simultaneous wireless information and power transfer. In particular, we address the transmit covariance optimization for the energy-harvesting maximization (EHM) problem under the constraint of secrecy rate and transmit power. The problem is nonconvex and hard to tackle. To circumvent it, we first resort to the Taylor series expansion to convert the problem into a convex optimization problem. Then, based on the analysis of its dual problem, an iterative algorithm, which includes a semiclosed-form solution, is proposed to handle this EHM problem. The scenario of imperfect channel state information of an energy receiver (the potential eavesdropper) is also considered. In this scenario, a Bernstein-type inequality-based iterative algorithm is proposed to deal with the challenging outage-constrained EHM problem. Simulation results demonstrate the efficiency of our proposed designs.
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.
In this article, downlink secure transmission in simultaneous information and power transfer (SWIPT) system enabled with massive multiple-input multiple-output (MIMO) is studied. A base station (BS) with a large number of antennas transmits energy and information signals to its intended users, but these signals are also received by an active eavesdropper. The users and eavesdropper employ a power splitting technique to simultaneously decode information and harvest energy. Massive MIMO helps the BS to focus energy to the users and prevent information leakage to the eavesdropper. The harvested energy by each user is employed for decoding information and transmitting uplink pilot signals for channel estimation. It is assumed that the active eavesdropper also harvests energy in the downlink and then contributes during the uplink training phase. Achievable secrecy rate is considered as the performance criterion and a closed-form lower bound for it is derived. To provide secure transmission, the achievable secrecy rate is then maximized through an optimization problem with constraints on the minimum harvested energy by the user and the maximum harvested energy by the eavesdropper. Numerical results show the effectiveness of using massive MIMO in providing physical layer security in SWIPT systems and also show that our closed-form expressions for the secrecy rate are accurate.