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International Conference on Wireless Communications and Signal Processing (WCSP)

Secrecy rate maximization for MISO system with energy harvesting and eavesdroppers

Sami Ahmed Haider, Yunlong Cai, Minjian Zhao

Published Oct 1, 2017• 2 citations
Publisher

Abstract

In this paper, we investigate the secrecy rate maximization problem for a multi user multiple-input single-output (MISO) broadcast interference communication system with simultaneous wireless information and power transfer (SWIPT), in the presence of external eavesdroppers. Assuming that the channel state information is perfectly known at the transmitter, the main aim is to maximize the secrecy rate of the system under signal to interference plus noise ratio (SINR), energy harvesting (EH) and total transmit power constraints. The original secrecy rate maximization problem is non-convex in terms of transmit beamforming matrix and power splitting ratios, usually solved via semi-definite relaxation. In order to circumvent this nonconvexity issue, we propose a concave-convex procedure (CCCP) based iterative algorithm, which provide a local maximum for the secrecy rate maximization. Simulation results are presented to validate the effectiveness of our proposed algorithm. It is demonstrated that our proposed CCCP based iterative algorithm achieves higher secrecy rate and has a lower computational complexity as compared to the conventional SDR technique.

DOI
10.1109/wcsp.2017.8171126

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In this paper, we investigate the secrecy rate maximization problem for a multi user multiple-input single-output (MISO) broadcast interference communication system with simultaneous wireless information and power transfer (SWIPT), in the presence of external eavesdroppers. Assuming that the channel state information is perfectly known at the transmitter, the main aim is to maximize the secrecy rate of the system under signal to interference plus noise ratio (SINR), energy harvesting (EH) and total transmit power constraints. The original secrecy rate maximization problem is non-convex in terms of transmit beamforming matrix and power splitting ratios, usually solved via semi-definite relaxation. In order to circumvent this nonconvexity issue, we propose a concave-convex procedure (CCCP) based iterative algorithm, which provide a local maximum for the secrecy rate maximization. Simulation results are presented to validate the effectiveness of our proposed algorithm. It is demonstrated that our proposed CCCP based iterative algorithm achieves higher secrecy rate and has a lower computational complexity as compared to the conventional SDR technique.
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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 paper, we design a secure transmission scheme for multiple-input single-output (MISO) broadcast channel with simultaneous wireless information and power transfer (SWIPT), where a multi-antenna transmitter simultaneously transmit independent confidential messages to multiple potentially malicious receivers, in the presence of external eavesdroppers. Our objective is to minimize the total transmit power while guaranteeing the security communication and energy harvesting constraints by jointly optimizing the transmit beamforming vectors, covariance of artificial noise, and power splitting ratios, which is non-convex optimization and hard to tackle. We first solve this non-convex problem by using the technique of semi-definite relaxation (SDR), and then prove that the relaxation is tight and thus achieves the globally optimal solution of the original problem. Simulation results are finally presented to demonstrate the performance of our proposed scheme.
This letter investigates a multiple-input single-output secrecy channel, where the legitimate user and the eavesdroppers employ a power splitting scheme for information decoding and energy harvesting (EH), simultaneously. An artificial noise is embedded to the information bearing signal to interfere the eavesdroppers and to harvest power by all receivers (i.e., legitimate user and eavesdroppers). We consider the robust secrecy rate maximization problem subject to the transmit power and the EH constraints by incorporating the norm-bounded channel uncertainty. This robust optimization problem is not convex, and thus, it can be reformulated as a convex one along with matrix transformations and convex conic optimization techniques, which is iteratively solved based on constrained concave-convex procedure-based algorithm. Finally, numerical results are provided to validate our proposed algorithm.
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.
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