Optimization for Maximizing Sum Secrecy Rate in MU-MISO SWIPT Systems

Alageli, Mahmoud; Ikhlef, Aïssa; Chambers, Jonathon A.

doi:10.1109/tvt.2017.2740282

Cited by 26 publications

(13 citation statements)

References 31 publications

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“…Without loss of generality, we assume that (22) is always feasible and focus on solving it. We use the exponential variable substitution method used in [32] and [33] to transform the logarithmic objective function of (22) into an equivalent linear function. By using the properties of logarithmic and exponential functions, the objective function of (22) can be expressed as log…”

Section: A Problem Formulationmentioning

confidence: 99%

Optimal Downlink Transmission for Cell-Free SWIPT Massive MIMO Systems With Active Eavesdropping

Alageli

Ikhlef

Alsifiany

et al. 2020

IEEE Trans.Inform.Forensic Secur.

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This paper considers secure simultaneous wireless information and power transfer (SWIPT) in cell-free massive multiple-input multiple-output (MIMO) systems. The system consists of a large number of randomly (Poisson-distributed) located access points (APs) serving multiple information users (IUs) and an information-untrusted dual-antenna active energy harvester (EH). The active EH uses one antenna to legitimately harvest energy and the other antenna to eavesdrop information. The APs are networked by a centralized infinite backhaul which allows the APs to synchronize and cooperate via a central processing unit (CPU). Closed-form expressions for the average harvested energy (AHE) and a tight lower bound on the ergodic secrecy rate (ESR) are derived. The obtained lower bound on the ESR takes into account the IUs' knowledge attained by downlink effective precoded-channel training. Since the transmit power constraint is per AP, the ESR is nonlinear in terms of the transmit power elements of the APs and that imposes new challenges in formulating a convex power control problem for the downlink transmission. To deal with these nonlinearities, a new method of balancing the transmit power among the APs via relaxed semidefinite programming (SDP) which is proved to be rank-one globally optimal is derived. A fair comparison between the proposed cell-free and the colocated massive MIMO systems shows that the cell-free MIMO outperforms the colocated MIMO over the interval in which the AHE constraint is low and vice versa. Also, the cell-free MIMO is found to be more immune to the increase in the active eavesdropping power than the colocated MIMO.

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Section: A Problem Formulationmentioning

confidence: 99%

Optimal Downlink Transmission for Cell-Free SWIPT Massive MIMO Systems With Active Eavesdropping

Alageli

Ikhlef

Alsifiany

et al. 2020

IEEE Trans.Inform.Forensic Secur.

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“…Our methods are compared to ZF method and SLNR method. The two methods are based on the schemes in [24] and [25], respectively, but the eavesdropping channels in these two methods are estimated in the same way as our VMD-SSRM method. The simulation parameters are set as shown in Table I, unless otherwise stated.…”

Section: Simulation and Analysismentioning

confidence: 99%

Robust Directional Modulation Design for Secrecy Rate Maximization in Multiuser Networks

Gui

Zhou

Shu

et al. 2020

IEEE Systems Journal

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In this paper, based on directional modulation (DM), robust beamforming matrix design for sum secrecy rate maximization is investigated in multi-user systems. The base station (BS) is assumed to have the imperfect knowledge of the direction angle toward each eavesdropper, with the estimation error following the Von Mises distribution. To this end, a Von Mises distribution-Sum Secrecy Rate Maximization (VMD-SSRM) method is proposed to maximize the sum secrecy rate by employing semi-definite relaxation and first-order approximation based on Taylor expansion to solve the optimization problem. Then in order to optimize the sum secrecy rate in the case of the worst estimation error of direction angle toward each eavesdropper, we propose a maximum angle estimation error-SSRM (MAEE-SSRM) method. The optimization problem is constructed based on the upper and lower bounds of the estimated eavesdropping channel related coefficient and then solved by the change of the variable method. Simulation results show that our two proposed methods have better sum secrecy rate than zero-forcing (ZF) method and signal-to-leakage-andnoise ratio (SLNR) method. Furthermore, the sum secrecy rate performance of our VMD-SSRM method is better than that of our MAEE-SSRM method.

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“…Si is still nonconvex, therefore, we use exponential variable substitution method [23], [32], [33] to convert min i R ′′…”

Section: A Information-untrusted Ehmentioning

confidence: 99%

“…Related Work: The concept of secure SWIPT has been studied for conventional MIMO/MISO systems in [20]- [23]. In [22], the authors proposed AN-aided SWIPT in a MISO system comprising a single IU and multiple untrusted EHs.…”

Section: Introductionmentioning

confidence: 99%

“…The considered problem was the maximization of the worstcase secrecy rate of the IU while maintaining a minimum level of individual harvested energy by each EH. The design in [22] was extended in [23] to consider sum secrecy rate maximization for multiple IUs. Latterly, the secure SWIPT design was extended to massive MIMO systems in [13]- [15].…”

Section: Introductionmentioning

confidence: 99%

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SWIPT Massive MIMO Systems With Active Eavesdropping

Alageli

Ikhlef

Chambers

2019

IEEE J. Select. Areas Commun.

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We consider the optimization of the downlink transmission for simultaneous wireless information and power transfer (SWIPT) in multi-cell massive multiple-input multipleoutput (MIMO) systems. The system comprises a two-antenna active energy harvester (EH) which is capable of legitimately harvesting energy via one antenna, and illegitimately and actively eavesdropping the signal intended for certain information user(s) (IU(s)) via the other antenna for the purpose of information decoding or energy harvesting. Thereby, the considered problems are: 1) when the EH eavesdrops for the purpose of information decoding, i.e., the EH is information-untrusted by the base station (BS), we propose to maximize the worst-case secrecy rate under a constraint on a worst-case average harvested energy (AHE); 2) when the EH eavesdrops one or multiple IUs for energy harvesting, i.e., the EH is information-trusted by the BS, we propose to maximize the sum-rate of the IUs under a constraint on a worst-case AHE by the EH. We derive asymptotic expressions for a lower bound on ergodic secrecy rate (ESR) and AHE in large system limit. Then, we use these results to optimize the power allocation for downlink SWIPT transmissions which include: information signals, artificial noise (AN) and energy signal towards the IUs, legitimate and illegitimate antennas of the EH, respectively. Simulation results show the accuracy of our asymptotic analysis. We show that there is a performance tradeoff between the worst-case ESR and the worst-case AHE. In addition, the impact of the combined legitimate/illegitimate operation of the EH on the SWIPT performance is evaluated.

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Optimization for Maximizing Sum Secrecy Rate in MU-MISO SWIPT Systems

Cited by 26 publications

References 31 publications

Optimal Downlink Transmission for Cell-Free SWIPT Massive MIMO Systems With Active Eavesdropping

Optimal Downlink Transmission for Cell-Free SWIPT Massive MIMO Systems With Active Eavesdropping

Robust Directional Modulation Design for Secrecy Rate Maximization in Multiuser Networks

SWIPT Massive MIMO Systems With Active Eavesdropping

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