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IEEE Globecom Workshops (GC Wkshps)

Secrecy Energy Efficiency in SWIPT Networks with Two-Layer Power-Splitting Receiver

Yang Lu, Ke Xiong, Jingxian Liu, Duohua Wang, Pingyi Fan, Zhangdui D. Zhong

Published Dec 1, 2018• 3 citations
Publisher

Abstract

This paper investigates the energy efficiency (EE) for a MISO simultaneous wireless information and power transfer (SWIPT) system where one transmitter intends to transmit information and energy to its legitimate power-splitting (PS) receivers while restricting the information leakage to an eavesdropper (Eve). To guarantee secure transmission, artificial noise (AN) is embedded into the transmit signals. The non-linear energy harvest (EH) model is adopted and a novel two-layer PS receiver architecture is proposed. Our goal is to maximize the system global secrecy EE (GSEE) by optimizing the transmit beamforming vectors, the AN covariance matrix and two-layer PS ratios under the EH requirement and the total available power constraints. To solve the non-convex optimization problem, the second-layer PS ratios are firstly optimized and then, an iterative solution framework is presented to jointly optimize the transmit beamforming vectors, the AN covariance matrix and the first-layer PS ratios. Simulation results demonstrate the validity and efficiency of our proposed solution approach. It is shown that the system GSEE has a saturation point and after passing the saturation point, it cannot be improved by increasing the transmit power anymore. It is also observed that compared with traditional PS receiver architecture, the proposed two-layer PS receiver architecture is able to achieve higher EH efficiency.

DOI
10.1109/glocomw.2018.8644181

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This paper investigates the energy efficiency (EE) for a MISO simultaneous wireless information and power transfer (SWIPT) system where one transmitter intends to transmit information and energy to its legitimate power-splitting (PS) receivers while restricting the information leakage to an eavesdropper (Eve). To guarantee secure transmission, artificial noise (AN) is embedded into the transmit signals. The non-linear energy harvest (EH) model is adopted and a novel two-layer PS receiver architecture is proposed. Our goal is to maximize the system global secrecy EE (GSEE) by optimizing the transmit beamforming vectors, the AN covariance matrix and two-layer PS ratios under the EH requirement and the total available power constraints. To solve the non-convex optimization problem, the second-layer PS ratios are firstly optimized and then, an iterative solution framework is presented to jointly optimize the transmit beamforming vectors, the AN covariance matrix and the first-layer PS ratios. Simulation results demonstrate the validity and efficiency of our proposed solution approach. It is shown that the system GSEE has a saturation point and after passing the saturation point, it cannot be improved by increasing the transmit power anymore. It is also observed that compared with traditional PS receiver architecture, the proposed two-layer PS receiver architecture is able to achieve higher EH efficiency.
This paper studies the secure beamforming design for simultaneous wireless information and power transfer in a multiple-input single-output broadcast channel with confidential messages and external eavesdroppers, where each receiver adopts the power splitting (PS) scheme to decode information and harvest energy concurrently, and it is also seen as a potential eavesdropper for messages not intended for it. Our objective is to minimize the total transmit power while guaranteeing the individual secrecy rate and energy harvesting constraints at each receiver by jointly optimizing transmit beamforming vectors, artificial noise covariance, and receive PS ratios. Both scenarios of perfect and imperfect channel state information (CSI) at the transmitter are considered. For the perfect CSI case, we propose a two-stage optimization approach to solve the original non-convex problem global optimality, and also provide a low-complexity suboptimal solution based on the particle swarm optimization algorithm. Furthermore, we also extend the above result to the colluding eavesdroppers scenario. For the imperfect CSI case, we propose a worst-case-based robust formulation, where the CSI errors are norm-bounded. With the aid of S-Procedure, we derive the equivalent forms for constraints and then transform the non-convex robust design into a convex optimization problem. Simulation results are finally presented to demonstrate the performance of our proposed schemes.
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 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.
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.
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.
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 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.