In this work, we investigate a joint transmit beamforming and artificial noise (AN) covariance matrix design in a multiple-input multiple-output (MIMO) cognitive radio (CR) downlink network with simultaneous wireless information and power transfer (SWIPT), where the malicious energy receivers (ERs) may decode the desired information and hence can be treated as potential eavesdroppers (Eves). In order to improve the secure performance of the transmission, AN is embedded to the information-bearing signal, which acts as interference to the Eves and provides energy to all receivers. Specifically, this joint design is studied under a practical non-linear energy harvesting (EH) model, our aim is to maximize the secrecy rate at the SR subject to the transmit power budget, EH constraints and quality of service (QoS) requirement. The original problem is not convex and challenging to be solved. To circumvent its intractability, an equivalent reformulation of this secrecy rate maximization (SRM) problem is introduced, wherein the resulting problem is primal decomposable and thus can be handled by alternately solving two convex subproblems. Finally, numerical results are presented to verify the effectiveness of our proposed scheme.
In this work, we investigate a joint transmit beamforming and artificial noise (AN) covariance matrix design in a multiple-input multiple-output (MIMO) cognitive radio (CR) downlink network with simultaneous wireless information and power transfer (SWIPT), where the malicious energy receivers (ERs) may decode the desired information and hence can be treated as potential eavesdroppers (Eves). In order to improve the secure performance of the transmission, AN is embedded to the information-bearing signal, which acts as interference to the Eves and provides energy to all receivers. Specifically, this joint design is studied under a practical non-linear energy harvesting (EH) model, our aim is to maximize the secrecy rate at the SR subject to the transmit power budget, EH constraints and quality of service (QoS) requirement. The original problem is not convex and challenging to be solved. To circumvent its intractability, an equivalent reformulation of this secrecy rate maximization (SRM) problem is introduced, wherein the resulting problem is primal decomposable and thus can be handled by alternately solving two convex subproblems. Finally, numerical results are presented to verify the effectiveness of our proposed 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 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 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.
This paper introduces an energy-efficient transmit design for multiple-input single-output (MISO) energy-harvesting cognitive radio (CR) networks in the presence of external eavesdroppers (Eves). Due to the inherent characteristics of CR network with simultaneous wireless information and power transfer (SWIPT), Eves may illegitimately access the primary user (PU) bands, and the confidential message is prone to be intercepted in wireless communications. Assuming the channel state information (CSI) of the Eves is not perfectly known at the transmitter, our approach to guaranteeing secrecy is to maximize the secrecy energy efficiency (SEE) by jointly designing the robust beamforming and the power splitting (PS) ratio, under the constraints of total transmit power, harvested energy at secondary receiver (SR) and quality of service (QoS) requirement. Specifically, a non-linear energy harvesting (EH) model is adopted for the SR, which can accurately characterize the property of practical RF-EH circuits. To solve the formulated non-convex problem, we first employ fractional programming theory and penalty function to recast it as an easy-to-handle parametric problem, and then deal with the non-convexity by applying S-Procedure and constrained concave convex procedure (CCCP), which enables us to exploit the difference of concave functions (DC) programming to seek the maximum worst-case SEE. Finally, numerical results are presented to verify the performance of the proposed scheme.
This paper consider a multiple-input multiple- output (MIMO) downlink system with simultaneous wireless information and power transfer (SWIPT). In this system, we provide secure communication by considering all non-linear energy receivers (ERs) as the potential eavesdroppers. We aim to design an optimal covariance matrix of the transmit signal based on the proposed outage-constrained secrecy rate maximization (OC-SRM) problem, where the proposed system keeps the probability of the secrecy rate outage and the harvested energy outage caused by uncertainties regarding the channel state information (CSI) below the given thresholds. The proposed maximization problem is non-convex and unlikely to be efficiently computable. To surmount the non-convexity of the proposed OC-SRM problem, we resort several transformations and approximations. In the partial channel uncertainty (PCU) model, we introduce auxiliary variables to transfer the Shannon capacity expressions into easy handled forms based on the concept of Fenchel conjugate arguments. As a compromise, we employ three safe approximation approaches to find the upper bounds of the probabilistic constraints. Moveover, an alternating optimization (AO) algorithm is proposed to solve the reformulated problem. The performance of the proposed design is efficiently validated by numerical results in our paper.
In this paper, we consider a multiple-input-multiple-output (MIMO) simultaneous wireless information and power transfer (SWIPT) system, which consists of a transmitter, a full-duplex (FD) desired receiver (DR) and multiple energy receivers (ERs), i.e., potential eavesdroppers. The transmitter and DR can send artificial noise (AN) and jamming signals to interfere and carry the energy to the ERs, respectively. Considering the imperfect channel state information (CSI) related to ERs, we aim to maximize the worst-case secrecy rate by jointly optimize the information covariance matrix, AN covariance matrix at the transmitter as well as the jamming covariance matrix at the DR, subject to their individual transmit power constraints and the minimum required power transferred to the ERs. In order to solve this non-convex and semi-infinite problem, we employ the S-procedure and propose a successive convex approximation (SCA) scheme based on Taylor series approximation, which can be efficiently solved by the proposed iterative method. Simulation results are finally presented to show the effectiveness of the new robust secrecy design.