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IEEE Access

Secure Transmission in SWIPT-Powered Two-Way Untrusted Relay Networks

Jiazhen Zhang, Xiaofeng Tao, Huici Wu, Xuefei Zhang

Published Jan 1, 2018• 45 citations
Publisher

Abstract

In this paper, we investigate the secure transmission in two-way untrusted amplify-and-forward relay networks with simultaneous wireless information and power transfer (SWIPT). Two secure SWIPT relaying strategies, namely, secure power splitting (SPS) and secure time switching (STS), are studied with the objective of secrecy rate (SR) and secure energy efficiency (SEE) maximization. First, the high signal-to-noise ratio approximations of SR and SEE are established, based on which non-convex SPS-based and convex STS-based SR maximization problems are formulated to jointly optimize the source transmit power and resource division ratio. Suboptimal solutions are obtained by employing Dinkelbach's method and Newton's method, respectively. Furthermore, to guarantee both the energy efficiency and secure quality of service (QoS) performance, SEE maximization problems are formulated with the consideration of the energy harvesting activation constraint and the target SR requirement. The intractable non-convex SEE maximization problems are reformulated as parameter programming, transformed to Lagrange dual problems, and finally solved by two SEE resource allocation algorithms with low complexity. Numerical results verify the convergence and effectiveness of the proposed algorithms and provide new insights into relaying strategy design and secure relay placement.

DOI
10.1109/access.2018.2804903

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In this paper, we investigate the secure transmission in two-way untrusted amplify-and-forward relay networks with simultaneous wireless information and power transfer (SWIPT). Two secure SWIPT relaying strategies, namely, secure power splitting (SPS) and secure time switching (STS), are studied with the objective of secrecy rate (SR) and secure energy efficiency (SEE) maximization. First, the high signal-to-noise ratio approximations of SR and SEE are established, based on which non-convex SPS-based and convex STS-based SR maximization problems are formulated to jointly optimize the source transmit power and resource division ratio. Suboptimal solutions are obtained by employing Dinkelbach's method and Newton's method, respectively. Furthermore, to guarantee both the energy efficiency and secure quality of service (QoS) performance, SEE maximization problems are formulated with the consideration of the energy harvesting activation constraint and the target SR requirement. The intractable non-convex SEE maximization problems are reformulated as parameter programming, transformed to Lagrange dual problems, and finally solved by two SEE resource allocation algorithms with low complexity. Numerical results verify the convergence and effectiveness of the proposed algorithms and provide new insights into relaying strategy design and secure relay placement.
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 the secure relay beamforming problem for simultaneous wireless information and power transfer (SWIPT) in an amplify-and-forward (AF) two-way relay network. We consider scenarios that the eavesdropper's channel state information (CSI) is and is not available. When the eavesdropper's CSI is available, our objective is to maximize the achievable secrecy sum rate under transmit power constraint and energy harvesting constraint. Since the optimization problem is nonconvex, we derive its performance upper bound, which requires 2-D search, where a semidefinite programming is solved in each step. We also propose an upper bound-based rank-one solution by employing the Gaussian randomization method. To reduce computational complexity, we transform the optimization problem into a difference-of-convex programming and propose a sequential parametric convex approximation (SPCA)-based iterative algorithm to find a locally optimal solution. Furthermore, we also propose a zero-forcing (ZF)-based suboptimal solution. Simulation results demonstrate that the upper bound-based rank-one solution archives the performance almost the same as the upper bound that has high computational complexity. The low-complexity SPCA-based locally optimal solution performs close to the upper bound. The ZF-based suboptimal solution has the lowest computational complexity among the proposed solutions. When the eavesdropper's CSI is not available, we propose an artificial noise-aided secure relay beamforming scheme.
Simultaneous wireless information and power transfer (SWIPT) is able to prolong the lifetime of energy-constrained wireless networks. In this paper, we study the security issue of a nonregenerative multiple-input multiple-out (MIMO) relay system with SWIPT. When the full channel state information (CSI) of the eavesdropper is available, we aim to maximize the secrecy rate under the source and relay transmit power constraints and energy-harvesting (EH) constraints at the multiple EH receivers by jointly designing the source and relay beamforming matrices, which is a nonconvex optimization and is still an open problem. In order to enhance the secrecy rate effectively, we first transform the optimization into a difference of convex programming and propose a sequential parametric convex approximation-based iterative algorithm which is able to achieve a local optimum. To reduce the complexity, we also propose a singular value decomposition (SVD)-generalized SVD-based method to simplify the optimization into a joint source and relay power allocation problem. The alternating optimization is employed to find a suboptimal solution of the joint power allocation problem. When the CSI of the eavesdropper is unknown, we propose an artificial-noise (AN) aided joint source and relay beamforming scheme, which can maximize the AN power to jam the eavesdropper under the limited source and relay transmit power and satisfy the quality of service of the receiver. Simulation results have shown the effectiveness of our proposed schemes.
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.
In this article, we raise the concern on secure energy efficiency (SEE) over the wireless-powered untrusted relay networks with nonlinear energy harvesting (EH). To achieve data confidentiality and secrecy performance enhancement concurrently, the untrusted relay can enable simultaneous energy signal reception and confidential information forwarding during the second phase, where no dedicated energy transmission phase or relaying signal splitting is needed for the energy supply. In particular, with the help of destination jamming, the relay can also harvest energy from source signal and jamming signal during the first phase, which is different from conventional relaying protocol that only harvests energy from source and recycled energy. Considering the nonlinear EH efficiency, our objective is to maximize the SEE through piecewise region selection and power allocation. To address this intractable nonconvex problem, a two-layer algorithm based on optimization decoupling, fractional programming, Lagrange dual decomposition and difference of convex functions (DC) programming is proposed. The core idea of the proposed algorithm is to convert the primary problem into simple subproblems by sequentially exploiting the above-mentioned optimization methods. Simulation results reveal the superior secrecy performance of the proposed scheme. The proposed algorithm achieves near-optimal solutions with faster convergence rate.
In this paper, we study the secure transmission scheme in multiple-input multiple-output (MIMO) communication systems with simultaneous wireless information and power transfer (SWIPT), in which both power splitting (PS) receiver and artificial noise (AN) are taken into account. We aim to maximize the achievable secrecy rate at the desired receiver by jointly designing precoding matrix, AN covariance matrix and PS ratio at the desired receiver, under the total transmit power constraint and the minimum energy harvesting constraints at all the receivers. The formulated optimization problem is nonconvex and hard to tackle. Then, by transforming this problem into a canonical DC (difference of convex function) programming, we propose an iterative method to solve this problem, and analyze the convergence of the proposed algorithm. Simulation results are provided to show the efficiency of our proposed scheme.