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IEEE International Conference on Communication Software and Networks

Secure Beamforming and Artificial Noise Design in Full-Duplex Wireless-Powered Relay Networks

Peipei Chen, Taoshen Li, Xing Fang

Published Jun 1, 2019• 4 citations
Publisher

Abstract

This thesis studies secure beamforming for simultaneous wireless information and power transfer (SWIPT) in full-duplex (FD) wireless-powered relay networks, in which the relay operates based on harvested energy from radio-frequency signals. We propose a joint AF beamforming and artificial noise (AB-AN) covariance matrix design with PS strategy to maximize the secrecy rate under harvesting energy constraints at the relay We assume that there is a PS device which splits the received signal power at relay for harvesting energy and receiving information. Since such a problem is nonconvex and hard to tackle, we propose a two-level optimization approach via the one-Dimension search and the semidefinite relaxation (SDR) technique. The proposed scheme is compared with AB scheme. Simulation results show that the proposed scheme outperforms the AB scheme.

DOI
10.1109/iccsn.2019.8905329

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This thesis studies secure beamforming for simultaneous wireless information and power transfer (SWIPT) in full-duplex (FD) wireless-powered relay networks, in which the relay operates based on harvested energy from radio-frequency signals. We propose a joint AF beamforming and artificial noise (AB-AN) covariance matrix design with PS strategy to maximize the secrecy rate under harvesting energy constraints at the relay We assume that there is a PS device which splits the received signal power at relay for harvesting energy and receiving information. Since such a problem is nonconvex and hard to tackle, we propose a two-level optimization approach via the one-Dimension search and the semidefinite relaxation (SDR) technique. The proposed scheme is compared with AB scheme. Simulation results show that the proposed scheme outperforms the AB scheme.
In this paper, we study secure beamforming for simultaneous wireless information and power transfer (SWIPT) in wireless-powered full-duplex (FD) relay networks. The relay assists transmission of confidential information, while simultaneously harvesting the energy with power switching scheme by the radio-frequency (RF) signals. We propose a joint amplify-and-forward beamforming (AB) and energy signal (AB-ES) with the receiver power splitting strategy (PS) scheme to maximize the secrecy rate under harvesting energy constraints. Since these constraints make the optimization problems become non-convex and hard to tackle. We propose a two-level optimization problem to solve this problem. The out part can be solved via the one-Dimensional search, and the inner part can be solved by semidefinite relaxation (SDR) technique. Simulation results show that the proposed scheme outperforms other schemes.
Abstract This paper studies the secure beamforming design for simultaneous wireless information and power transfer (SWIPT) in a amplify-and-forward (AF) relay networks with multiple users and eavesdroppers. Each user node adopts the power splitting (PS) scheme to decode information and harvest energy simultaneously. Our objective is to minimize the total relay transmit power under the constraints of secure transmission rate and energy harvesting requirements by jointly optimizing the beamforming matrix, artificial noise covariance matrix and PS ratios. For this non-convex problem, we propose a two-stage optimization approach to convert the original problem into two sub-problems. The first subproblem uses semidefinite relaxation (SDR) technique to transform the original problem into a convex problem, and then finds the optimal solution of the second subproblem through k-dimensional exhaustive search algorithm. Furthermore, we also propose a low complexity suboptimal solution scheme based on particle swarm optimization (PSO) algorithm. Simulation results show that the proposed scheme saves transmitting power and achieves better performance than other schemes.
In this paper, we investigate physical layer security for simultaneous wireless information and power transfer in amplify-and-forward relay networks. We propose a joint robust cooperative beamforming and artificial noise scheme for secure communication and efficient wireless energy transfer. Specifically, by treating the energy receiver as a potential eavesdropper and assuming that only imperfect channel state information can be obtained, we formulate an optimization problem to maximize the worst-case secrecy rate between the source and the legitimate information receiver under both the power constraint at the relays and the wireless power harvest constraint at the energy receiver. Since such a problem is non-convex and hard to tackle, we propose a two-level optimization approach which involves a one-dimensional search and semidefinite relaxation. Simulation results show that the proposed robust scheme achieves better worst-case secrecy rate performance than other schemes.
In this paper, we investigate the physical layer security for amplify-and-forward relay networks with simultaneous wireless information and power transfer. Specifically, by considering the dual-functional desired receiver, which is capable of decoding information and energy harvesting (EH), and assuming that only imperfect eavesdroppers' channel state information can be attained, we propose a joint robust cooperative beamforming, artificial noise, and power splitting scheme. We formulate the relay power minimization problem under both the secrecy rate constraint and the EH constraint, which is non-convex and hard to tackle. To tackle this problem, we propose a two-level optimization approach, which involves 1-D search and the semi-definite relaxation. In addition, we testify that the SDR can obtain the rank-one optimal solution. Simulation results show that the proposed robust scheme achieves better secrecy performance than other schemes.
In this paper, we investigate cooperative secure beamforming for simultaneous wireless information and power transfer (SWIPT) in amplify-and-forward (AF) relay networks. We propose a joint cooperative beamforming (CB) and energy signal (CB-ES) scheme for providing both secure communication and efficient wireless energy transfer. By considering colluding eavesdroppers with imperfect channel state information (CSI), we formulate an optimization problem for maximizing the secrecy rate between the source and the legitimate information receiver (IR) under both the power constraints at the relays and the wireless power transfer constraint at the energy-harvesting receiver (ER). Since such a problem is nonconvex and hard to tackle, we propose a two-level optimization approach that involves a 1-D search and the semidefinite relaxation (SDR) technique to solve this problem. The proposed robust scheme is compared with some other nonrobust schemes, such as a CB and artificial noise (CB-AN) scheme and a perfect scheme. Simulation results show that the proposed robust scheme achieves better worst-case secrecy rate performance than the other nonrobust schemes and the CB-AN scheme, while it approaches the perfect scheme.
This paper investigates an energy-constrained relay-assisted secure communication system in the presence of a legitimate source-destination pair and a passive eavesdropper with imperfect channel state information (CSI). The energy-constrained relay exploits a power splitting (PS) protocol to simultaneously harvest energy and decode information from the received signal from the source, and then forwards the confidential signal to the full-duplex (FD) destination while it simultaneously transmits artificial noise (AN) to confuse the passive eavesdropper. This robust beamforming design is developed by maximizing the secrecy rate under the constraints of energy harvesting (EH) requirement at the relay and AN transmit power at the destination. Specifically, we formulate the joint relay beamforming and PS ratio as well as the AN power optimization as a non-convex quadratically-constrained problem. In order to circumvent this non-convexity issue, we decompose the original problem into three subproblems which can be determined by the proposed semidefinite relaxation (SDR) and successive convex optimization methods. Furthermore, we derive closed-form expressions for the optimal solutions of each subproblem. Finally, the original non-convex problem can be solved through a convergence guaranteed iterative algorithm. Simulation results are provided to demonstrate the effectiveness and superior performance of the proposed robust design compared with the benchmark schemes.