This paper investigates the secure transmit design for simultaneous wireless information and power transfer system under the non-linear energy harvesting (EH) model, where a transmitter sends confidential information and transfers energy to multiple information receivers (IRs) and EH receivers (ERs) with the existence of multiple eavesdroppers (Eves). To prevent confidential information leakage, multiple artificial redundant signals (MARSs) are embedded in the transmit signals. The goal is to minimize the total transmit power by jointly optimizing transmit beamforming vectors and the covariance matrixes of MARSs, such that the minimal information rate and EH requirements at IRs and ERs are guaranteed while making the received signal-to-Interference ratio at ERs and Eves lower than their information decoding thresholds. Both the non-robust and the robust designs are studied. For the non-robust design, the optimal solution is derived. For the robust design, an approximate optimal solution is obtained by using Gaussian randomization procedure. Simulation results show that compared with traditional non-MARS-aided beamforming design, our proposed design is superior in terms of the total required transmit power. It also shows that employing the non-linear EH model can avoid false output power at the ERs and/or save power at the transmitter.
This paper investigates the secure transmit design for simultaneous wireless information and power transfer system under the non-linear energy harvesting (EH) model, where a transmitter sends confidential information and transfers energy to multiple information receivers (IRs) and EH receivers (ERs) with the existence of multiple eavesdroppers (Eves). To prevent confidential information leakage, multiple artificial redundant signals (MARSs) are embedded in the transmit signals. The goal is to minimize the total transmit power by jointly optimizing transmit beamforming vectors and the covariance matrixes of MARSs, such that the minimal information rate and EH requirements at IRs and ERs are guaranteed while making the received signal-to-Interference ratio at ERs and Eves lower than their information decoding thresholds. Both the non-robust and the robust designs are studied. For the non-robust design, the optimal solution is derived. For the robust design, an approximate optimal solution is obtained by using Gaussian randomization procedure. Simulation results show that compared with traditional non-MARS-aided beamforming design, our proposed design is superior in terms of the total required transmit power. It also shows that employing the non-linear EH model can avoid false output power at the ERs and/or save power at the transmitter.
This work studies a beamforming design for down-link transmission of a multi-user multiple-input single-output (MISO) system where each legitimate user employs a power splitting (PS) based simultaneous wireless information and power transfer (SWIPT) technique. The transmitter intends to send confidential information to its legitimate users in the presence of purely unknown eavesdroppers. Since the transmitter does not have any knowledge of the eavesdroppers' channel state information (CSI), we consider an artificial noise (AN) approach to establishing secure communication. This beamforming design is developed by maximizing the AN power to interfere with the eavesdropper as much as possible. Based on the assumption of imperfect CSI of legitimate users at the transmitter, two robust design approaches for the joint beamforming and PS ratio have been studied to maximize the AN power under both energy harvesting (EH) and signal-to-interference-plus-noise ratio (SINR) requirements at each legitimate user. In the first robust design, we consider the bounded channel uncertainties, and employ semidefinite relaxation (SDR) and a linear matrix inequality (LMI) representation to transform the original problem into a semidefinite program (SDP). In the second robust design, we consider the statistical channel uncertainties, and show that the proposed problem can be reformulated into another form of SDP through both SDR and Bernstein-type inequality. In addition, the non-linear energy harvesting (EH) model is incorporated in this work as it could reflect the characteristics of practical radio frequency(RF)-EH conversion circuit. Simulation results have been provided to demonstrate the performance of our proposed robust designs.
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.
In this letter, we investigate the energy efficiency optimization for simultaneous wireless information and power transfer in multiple-input-multiple-output wiretapping systems, which consist of one transmitter, multiple desired receivers (DRs), and multiple eavesdroppers. Specifically, considering non-linear energy harvesting model, we aim to maximize the ratio of the total harvested power at the DRs to the total power consumption at the transmitter, e.g., the harvested power efficiency, by jointly designing the transmit precoding matrix, the artificial noise covariance and the power splitting ratios, subject to the secrecy rate constraint. To solve the formulated highly non-convex non-linear single-ratio problem, we propose a successive convex approximation and constrained concave convex procedure-based iterative algorithm. Finally, our proposed algorithm is validated by some representative numerical results.
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 study an energy harvesting scheme for a multiple-input-single-output secrecy channel under imperfect channel state information case with either deterministic and statistical channel uncertainties. The system consists of one multi-antenna transmitter, several multi-antenna energy receivers (ERs) and one single-antenna co-located receiver (CR) who adopts a power splitter to decode information and harvest power simultaneously. We consider the artificial noise (AN) embedded information-bearing signal to interfere potential eavesdroppers (i.e., ERs) and capture the harvested power. We perform joint optimization for the masked beamforming matrix, the AN covariance matrix and the power splitting ratio, such that the transmit power is minimized to satisfy the target secrecy rate of the CR, the total transmit power and the energy harvesting constraints for the CR and the ERs. By incorporating norm-bounded channel uncertainty model, we propose a robust joint design method to obtain the optimal solution. Also, a suboptimal algorithm for the outage constrained robust optimization problem is proposed by adopting the Bernstein-type inequality. Furthermore, the tightness of the relaxation for the proposed schemes are verified by showing that the optimal solution of the relaxed problem is rank-one. Finally, simulation results are presented to validate the performance of our proposed schemes.
This letter considers simultaneous wireless information and power transfer (SWIPT) in multiple-input-single-output downlink systems in which a multiantenna transmitter sends a secret message to a single-antenna information receiver (IR) with multiple single-antenna energy receivers (ERs). We aim to maximize the harvested energy by the ERs while maintaining the signal-to-interference-and-noise ratio (SINR) threshold at the IR and keeping the message secure from possible eavesdropping by the ERs by suppressing their SINRs. Both scenarios of perfect and imperfect channel state information at the transmitter are studied. Using semidefinite relaxation techniques, we show that there always exists a rank-one optimal solution for the IR, i.e., transmit beamforming is optimal for the IR.