Secrecy Rate Optimizations for a MISO Secrecy Channel with Multiple Multiantenna Eavesdroppers

Chu, Zheng; Xing, Hong; Johnston, Martin; Goff, Stan

doi:10.1109/twc.2015.2472405

Cited by 117 publications

(80 citation statements)

References 37 publications

(44 reference statements)

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“…As a complementary solution, physical-layer security has attracted significant attention for safeguarding wireless networks. In this line of research, physical-layer security for the multiple-input singleoutput channels [6], multiple-input multiple-output channels [7], relay channels [8], interference channels [9] and cognitive channels [10] have been well pursued. Additionally, the concept of directional modulation is recently exploited to enhance the security from a practical implementation perspective [11].…”

mentioning

confidence: 99%

Robust Chance-Constrained Secure Transmission for Cognitive Satellite–Terrestrial Networks

Fei

Chu

et al. 2018

IEEE Trans. Veh. Technol.

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121

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Abstract-Cognitive satellite-terrestrial networks (CSTNs) have been recognized as a promising network architecture for addressing spectrum scarcity problem in next-generation communication networks. In this paper, we investigate the secure transmission for CSTNs where the terrestrial base station (BS) serving as a green interference resource is introduced to enhance the security of the satellite link. Adopting a stochastic model for the channel state information (CSI) uncertainty, we propose a secure and robust beamforming framework to minimize the transmit power, while satisfying a range of outage (probabilistic) constraints concerning the signal-to-interference-plus-noise ratio (SINR) recorded at the satellite user and the terrestrial user, the leakage-SINR recorded at the eavesdropper, as well as the interference power recorded at the satellite user. The resulting robust optimization problem is highly intractable and the key observation is that the highly intractable probability constraints can be equivalently reformulated as the deterministic versions with Gaussian statistics. In this regard, we develop two robust reformulation methods, namely S-Procedure and Bernstein-type inequality restriction techniques, to obtain a safe approximate solution. In the meantime, the computational complexities of the proposed schemes are analyzed. Finally, the effectiveness of the proposed schemes are demonstrated by numerical results with different system parameters.

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confidence: 99%

Robust Chance-Constrained Secure Transmission for Cognitive Satellite–Terrestrial Networks

Fei

Chu

et al. 2018

IEEE Trans. Veh. Technol.

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121

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“…Perform a one-dimensional search over ν to obtain the optimal values (ν * , Θ(λ i , ν * )) for the outer problem in (43), where each Θ(λ i , ν) is obtained by solving the inner problem in (50); 4: Retrieve the corresponding Q * s through (46); 5:…”

Section: Simulation Resultsmentioning

confidence: 99%

Energy Efficiency Optimization for Secure Transmission in MISO Cognitive Radio Network With Energy Harvesting

Zhang¹,

Cumanan²,

Thiyagalingam³

et al. 2019

IEEE Access

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In this paper, we investigate different secrecy energy efficiency (SEE) optimization problems in a multiple-input single-output underlay cognitive radio (CR) network in the presence of an energy harvesting receiver. In particular, these energy efficient designs are developed with different assumptions of channels state information (CSI) at the transmitter, namely perfect CSI, statistical CSI and imperfect CSI with bounded channel uncertainties. In particular, the overarching objective here is to design a beamforming technique maximizing the SEE while satisfying all relevant constraints linked to interference and harvested energy between transmitters and receivers. We show that the original problems are non-convex and their solutions are intractable. By using a number of techniques, such as non-linear fractional programming and difference of concave (DC) functions, we reformulate the original problems so as to render them tractable. We then combine these techniques with the Dinkelbach's algorithm to derive iterative algorithms to determine relevant beamforming vectors which lead to the SEE maximization. In doing this, we investigate the robust design with ellipsoidal bounded channel uncertainties, by mapping the original problem into a sequence of semidefinite programs This paper has been presented in part at the IEEE Wireless Communications and Signal Processing (WCSP), October 11-13, 2017 [1]. M. Zhang is with the ). Z. Ding is with the School of Electrical and Electronic Engineering, The University of Manchester, Manchester, UK (email: zhiguo.ding@manchester.ac.uk). O. A. Dobre is with the employing the semidefinite relaxation, non-linear fractional programming and S-procedure. Furthermore, we show that the maximum SEE can be achieved through a search algorithm in the single dimensional space. Numerical results, when compared with those obtained with existing techniques in the literature, show the effectiveness of the proposed designs for SEE maximization.

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“…Another curve is related to Bernstein inequality–based method. See, for example, the works of Chu et al and Xu et al in order to study this approach.…”

Section: Results and Evaluationmentioning

confidence: 99%

Probabilistic‐based secrecy rate maximisation for MIMOME wiretap channels: Towards novel convexification procedures—Part II

Zamanipour¹

2018

Trans Emerging Tel Tech

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This paper extends our previous work on multiple‐input–multiple‐output multiantenna eavesdropper–based wiretap channels aimed at fundamentally proposing optimally secure frameworks. This extension is appropriately conducted providing 2 newly asymptotic bounds for the secrecy outage capacity. Such proposed schemes should be necessarily taken into consideration owing to channel uncertainty sets in relation to the eavesdropping fusion center. Our first resultant closed‐form solution, which is mathematically performed according to Hanson‐Wright inequality, is totally tight as well; something that can be technically assigned to other ergodicity‐driven equilibria. Specifically, our solution's outperformance is highlighted with regard to a significantly more adequate secrecy capacity in the low signal‐to‐noise‐ratio regime. Such outperformance is efficiently guaranteed due to assigning optimally convex paradigms regarding the concentration‐of‐measure‐based inequality aforementioned. Additionally, our framework has a markedly acceptable computational complexity compared with our previous work. The latter characteristic is straightforwardly highlighted in parallel with a considerably acceptable computational error as well. Finally, we optimally generalise our framework to dynamically fast fading processes in terms of the secondly closed‐form asymptotic bound. At the end of the discussion, simulation‐based analytical results principally authenticate our contribution's efficiency and tightness.

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Secrecy Rate Optimizations for a MISO Secrecy Channel with Multiple Multiantenna Eavesdroppers

Cited by 117 publications

References 37 publications

Robust Chance-Constrained Secure Transmission for Cognitive Satellite–Terrestrial Networks

Robust Chance-Constrained Secure Transmission for Cognitive Satellite–Terrestrial Networks

Energy Efficiency Optimization for Secure Transmission in MISO Cognitive Radio Network With Energy Harvesting

Probabilistic‐based secrecy rate maximisation for MIMOME wiretap channels: Towards novel convexification procedures—Part II

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