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IEICE Transactions on Communications

Energy Efficiency Optimization for Secure SWIPT System

Chao Meng, Gang Wang, Bingjian YAN, Yongmei LI

Published Oct 28, 2019• 2 citations
Publisher

Abstract

This paper investigates the secrecy energy efficiency maximization (SEEM) problem in a simultaneous wireless information and power transfer (SWIPT) system, wherein a legitimate user (LU) exploits the power splitting (PS) scheme for simultaneous information decoding (ID) and energy harvesting (EH). To prevent interference from eavesdroppers on the LU, artificial noise (AN) is incorporated into the confidential signal at the transmitter. We maximize the secrecy energy efficiency (SEE) by joining the power of the confidential signal, the AN power, and the PS ratio, while taking into account the minimum secrecy rate requirement of the LU, the required minimum harvested energy, the allowed maximum radio frequency transmission power, and the PS ratio. The formulated SEEM problem involves nonconvex fractional programming and is generally intractable. Our solution is Lagrangian relaxation method than can transform the original problem into a two-layer optimization problem. The outer layer problem is a single variable optimization problem with a Lagrange multiplier, which can be solved easily. Meanwhile, the inner layer one is fractional programming, which can be transformed into a subtractive form solved using the Dinkelbach method. A closed-form solution is derived for the power of the confidential signal. Simulation results verify the efficiency of the proposed SEEM algorithm and prove that AN-aided design is an effective method for improving system SEE.

DOI
10.1587/transcom.2019ebp3181

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This letter studies energy efficient optimization problem for a general multiple-input multiple-output multiple-eavesdropper system, in which the legitimate receiver exploits a power splitting (PS) scheme for decoding information and harvesting energy simultaneously. In order to cripple the eavesdroppers' reception and provide energy for the legitimate receiver to harvest, the transmitter also emits artificial noise (AN) in the transmission. Our interest in this letter lies in the joint design of the transmit covariance matrices and PS ratio, such that the secrecy energy efficiency (SEE) is maximized. The SEE maximization problem is a nonconvex fractional problem. To handle it, we resort to the fractional programming to transform its objective function into a more tractable subtractive form. Furthermore, we show that the resultant problem is primal decomposable by recasting it as an equivalent form amenable to alternating optimization. Numerical results indicate that incorporating AN and PS is beneficial to the SEE enhancement.
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.
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.
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 study simultaneous wireless information and power transfer (SWIPT) in orthogonal frequency division multiple access (OFDMA) systems with the coexistence of information receivers (IRs) and energy receivers (ERs). The IRs are served with best-effort secrecy data and the ERs harvest energy with minimum required harvested power. To enhance the physical layer security for IRs and yet satisfy energy harvesting requirements for ERs, we propose a new frequency-domain artificial noise (AN) aided transmission strategy. With the new strategy, we study the optimal resource allocation for the weighted sum secrecy rate maximization for IRs by power and subcarrier allocation at the transmitter. The studied problem is shown to be a mixed integer programming problem and thus nonconvex, while we propose an efficient algorithm for solving it based on the Lagrange duality method. To further reduce the computational complexity, we also propose a suboptimal algorithm of lower complexity. The simulation results illustrate the effectiveness of proposed algorithms as compared against other heuristic schemes.
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.