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arXiv:1608.08576 · IEEE Transactions on Information Forensics and Security

Probabilistically Robust SWIPT for Secrecy MISOME Systems

Muhammad R. A. Khandaker, Kai‐Kit Wong, Yangyang Zhang, Zhongbin Zheng

Published Sep 20, 2016• 61 citations
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Abstract

This paper considers simultaneous wireless information and power transfer in a multiple-input single-output downlink system consisting of one multi-antenna transmitter, one single-antenna information receiver, multiple multi-antenna eavesdroppers (Eves), and multiple single-antenna energy-harvesting receivers (ERs). The main objective is to keep the probability of the legitimate user's achievable secrecy rate outage as well as the ERs' harvested energy outage caused by channel state information uncertainties below some prescribed thresholds. As is well known, the secrecy rate outage constraints present a significant analytical and computational challenge. Incorporating the energy harvesting outage constraints only intensifies that challenge. In this paper, we address this challenging issue using convex restriction approaches which are then proved to yield rank-one optimal beamforming solutions. Numerical results reveal the effectiveness of the proposed schemes.

DOI
10.1109/tifs.2016.2611478

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This paper considers simultaneous wireless information and power transfer in a multiple-input single-output downlink system consisting of one multi-antenna transmitter, one single-antenna information receiver, multiple multi-antenna eavesdroppers (Eves), and multiple single-antenna energy-harvesting receivers (ERs). The main objective is to keep the probability of the legitimate user's achievable secrecy rate outage as well as the ERs' harvested energy outage caused by channel state information uncertainties below some prescribed thresholds. As is well known, the secrecy rate outage constraints present a significant analytical and computational challenge. Incorporating the energy harvesting outage constraints only intensifies that challenge. In this paper, we address this challenging issue using convex restriction approaches which are then proved to yield rank-one optimal beamforming solutions. Numerical results reveal the effectiveness of the proposed schemes.
This paper considers simultaneous wireless information apower transfer (SWIPT) in a multiple-input multiple-output (MIMO) wiretapnd power transfer (SWIPT) in a multiple-input multiple-output (MIMO) wiretap channel with energy harvesting receivers. The main objective is to keep the probability of the legitimate user's achievable secrecy rate outage as well as the energy receivers' harvested energy outage as caused by CSI uncertainties below given thresholds. This probabilistic-constrained secrecy rate maximization problem presents a significant analytical and computational challenge since any closed-form for the probabilistic constraints with log-det functions is intractable. In this paper, we address this challenging issue using codeviation inequalitiesnvex restrictions. In particular, we derive decomposition-based large deviation inequalities to transform the probabilistic constraints into second-order cone (SOC) constraints which are easier to handle. Then we show that a robust safe solution can be obtained through solving two convex sub-problems in an alternating fashion.
This letter considers simultaneous wireless information and power transfer (SWIPT) in multiple-input-single-output downlink systems in which a multiantenna transmitter sends a secret message to a single-antenna information receiver (IR) with multiple single-antenna energy receivers (ERs). We aim to maximize the harvested energy by the ERs while maintaining the signal-to-interference-and-noise ratio (SINR) threshold at the IR and keeping the message secure from possible eavesdropping by the ERs by suppressing their SINRs. Both scenarios of perfect and imperfect channel state information at the transmitter are studied. Using semidefinite relaxation techniques, we show that there always exists a rank-one optimal solution for the IR, i.e., transmit beamforming is optimal for the IR.
In this letter, we investigate the simultaneous wireless information and power transfer in a multiple-input-single-output downlink system which consists of one multi-antenna transmitter, one single-antenna desired receiver, and multiple single-antenna eavesdroppers. Specifically, we investigate the outage-constrained secrecy rate maximization by jointly designing the transmit beamforming vector and the power splitting ratio with statistical channel uncertainties. To handle the formulated non-convex problem, we resort to semi-definite relaxation (SDR) and the Bernstein-type inequality to transform the outage constraints into a deterministic form. Then, the original problem can be efficiently solved by alternately optimizing two convex subproblems. In addition, we testify that the SDR can obtain the rank-one optimal solution. Finally, our proposed algorithm is validated by some representative numerical results.
This paper considers simultaneous wireless information and power transfer (SWIPT) in multiple-input single-output (MISO) downlink systems in which a multi-antenna transmitter sends a secret message to a single-antenna information receiver (IR) and power to multiple single-antenna energy receivers (ERs) in presence of external eavesdroppers. We aim to maximize the harvested energy by the ERs while maintaining the signal-to-interference and noise ratio (SINR) threshold at the IR and keeping the message secure from possible eavesdropping by the malicious attackers by interfering their reception. Both scenarios of perfect and imperfect channel state information (CSI) at the transmitter are studied. Using semidefinite relaxation (SDR) techniques, we show that a rank-one optimal beamforming solution can always be constructed for the IR.
In this paper, we study an energy harvesting scheme for a multiple-input-single-output secrecy channel under imperfect channel state information case with either deterministic and statistical channel uncertainties. The system consists of one multi-antenna transmitter, several multi-antenna energy receivers (ERs) and one single-antenna co-located receiver (CR) who adopts a power splitter to decode information and harvest power simultaneously. We consider the artificial noise (AN) embedded information-bearing signal to interfere potential eavesdroppers (i.e., ERs) and capture the harvested power. We perform joint optimization for the masked beamforming matrix, the AN covariance matrix and the power splitting ratio, such that the transmit power is minimized to satisfy the target secrecy rate of the CR, the total transmit power and the energy harvesting constraints for the CR and the ERs. By incorporating norm-bounded channel uncertainty model, we propose a robust joint design method to obtain the optimal solution. Also, a suboptimal algorithm for the outage constrained robust optimization problem is proposed by adopting the Bernstein-type inequality. Furthermore, the tightness of the relaxation for the proposed schemes are verified by showing that the optimal solution of the relaxed problem is rank-one. Finally, simulation results are presented to validate the performance of our proposed schemes.
In this paper, we consider a multiuser multiple-input multiple-output (MIMO) downlink communication system with simultaneous wireless information and power transfer (SWIPT). In particular, we focus on a realistic and efficient multi-receiver multi-eavesdropper MIMO SWIPT system, in which the channel state information (CSI) of each legitimate receiver and energy receiver (i.e., potential eavesdropper) is partially known to the transmitter. Based on this, we propose a robust artificial noise (AN)-aided secure transmission scheme for the system, where the channel uncertainties are modeled by the worst-case model. In the proposed scheme, we aim to maximize the worst-case achievable secrecy rate under the transmit power constraint and the energy harvesting (EH) constraint, by jointly optimizing the transmit precoding matrix and the AN covariance matrix. We utilize the S-Procedure and Taylor series approximation to transform the non-convex problem. Then, we apply the interior point method to tackle the transformed convex problem, obtaining the approximate optimal matrices and the corresponding maximum worst-case secrecy rate. Simulation results show that our proposed scheme achieves significant performance improvements in terms of convergence and the worst-case achievable secrecy rate.