Intelligent Reflecting Surface Aided Multi-Antenna Secure Transmission

Chu, Zheng; Hao, Wanming; Xiao, Pei; Shi, Jia

doi:10.1109/lwc.2019.2943559

Cited by 246 publications

(137 citation statements)

References 19 publications

(36 reference statements)

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“…In [193], the authors consider an RIS-aided wiretap channel model, and study the problem of minimizing the power consumption under a minimum secrecy rate constraint and by optimizing the transmit power and the RIS phase shifts. The resulting optimization problem is shown to be nonconvex, and is tackled by means of semi-definite relaxation and alternating optimization between the transmit powers and the RIS phase shifts.…”

Section: K Physical Layer Securitymentioning

confidence: 99%

Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead

Renzo

Zappone

Debbah

et al. 2020

IEEE J. Select. Areas Commun.

1,796

845

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What is a reconfigurable intelligent surface? What is a smart radio environment? What is a metasurface? How do metasurfaces work and how to model them? How to reconcile the mathematical theories of communication and electromagnetism? What are the most suitable uses and applications of reconfigurable intelligent surfaces in wireless networks? What are the most promising smart radio environments for wireless applications? What is the current state of research? What are the most important and challenging research issues to tackle? These are a few of the many questions that we investigate in this short opus, which has the threefold objective of introducing the emerging research field of smart radio environments empowered by reconfigurable intelligent surfaces, putting forth the need of reconciling and reuniting C. E. Shannon's mathematical theory of communication with G. Green's and J. C. Maxwell's mathematical theories of electromagnetism, and reporting pragmatic guidelines and recipes for employing appropriate physics-based models of metasurfaces in wireless communications.

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Section: K Physical Layer Securitymentioning

confidence: 99%

Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead

Renzo

Zappone

Debbah

et al. 2020

IEEE J. Select. Areas Commun.

1,796

845

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“…Fewer works, [49]- [51], considered the case when multiple eavesdroppers are attacking a single legitimate user as shown in Fig. 3-(b).…”

Section: ) Multiple Bobs or Evesmentioning

confidence: 99%

“…It is shown that the use of AN jamming requires fewer reflecting elements on the RIS in order to maintain a specific SR threshold. In a related context, where the power efficiency is considered, the authors in [51], study the role of RIS in minimizing the transmitted power while maintaining a secrecy level. Considering the non-convex nature of the problem, an AO algorithm and an SDR method to optimize the secure and power-efficient transmission are proposed.…”

Section: ) Multiple Bobs or Evesmentioning

confidence: 99%

Smart and Secure Wireless Communications via Reflecting Intelligent Surfaces: A Short Survey

Almohamad

Tahir

Al‐Kababji

et al. 2020

IEEE Open J. Commun. Soc.

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With the emergence of the internet of things (IoT) technology, wireless connectivity should be more ubiquitous than ever. In fact, the availability of wireless connection everywhere comes with security threats that, unfortunately, cannot be handled by conventional cryptographic solutions alone, especially in heterogeneous and decentralized future wireless networks. In general, physical layer security (PLS) helps in bridging this gap by taking advantage of the fading propagation channel. Moreover, the adoption of reconfigurable intelligent surfaces (RIS) in wireless networks makes the PLS techniques more efficient by involving the channel into the design loop. In this paper, we conduct a comprehensive literature review on the RIS-assisted PLS for future wireless communications. We start by introducing the basic concepts of RISs and their different applications in wireless communication networks and the most common PLS performance metrics. Then, we focus on the review and classification of RIS-assisted PLS applications, exhibiting multiple scenarios, system models, objectives, and methodologies. In fact, most of the works in this field formulate an optimization problem to maximize the secrecy rate (SR) or secrecy capacity (SC) at a legitimate user by jointly optimizing the beamformer at the transmitter and the RIS's coefficients, while the differences are in the adopted methodology to optimally/sub-optimally approach the solution. We finalize this survey by presenting some insightful recommendations and suggesting open problems for future research extensions.

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“…The RA problems for IRS-enabled wireless networks have attracted great attention, in which the major efforts have been put on enhancing system secrecy and spectrum efficiency. For the single-user IRS-based multipleinput single-output (MISO) system with single eavesdropper, transmit power minimization and secrecy rate maximization have been studied in [11] and [12], respectively. Extended to the multi-user scenario, the secrecy rate maximization under one eavesdropper and the max-min secrecy rate under multiple eavesdroppers have been discussed in [13] and [14], respectively.…”

Section: A Related Workmentioning

confidence: 99%

“…A separate wireless control link serves for information exchange between the IRS controller and the SBS on the channel state information (CSI) and other information needed for implementing the joint design of the SBS transmit power and IRS reflection with the QoS guaranteed for the MCU [20]. We assume that the CSI is available at the BS via channel training or feedback from the users and the IRS [11], [12].…”

Section: A System Modelmentioning

confidence: 99%

Resource Allocation for Intelligent Reflecting Surface Enabled Heterogeneous Networks

Xu¹,

Qin²,

Zhao³

et al. 2020

Preprint

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Intelligent reflecting surface (IRS)-enabled communication systems provide higher system capacity and spectral efficiency by reflecting the incident signals from transmitters in a low-cost passive reflecting way. However, it poses new challenges in resource allocation due to surrounding interference and phase shift, especially when IRS is employed in heterogeneous networks (HetNets). In this paper, a joint power allocation and phase shift optimization problem is studied for the downlink IRS-enabled HetNet, in which the IRS is deployed to enhance the communications between small cell users (SCUs) and associated base station (BS). The signal-to-interference-plus-noise ratio (SINR) received at the SCU is maximized by jointly optimizing the transmit power of the small-cell BS and the phase shift of the IRS, subject to the constraints on the minimum SINR requirement of the macro-cell user (MCU) and the phase shift. Although the formulated problem is non-convex, we develop an optimal power allocation and the IRS's passive array coefficient solution for the single-user scenario. For the multi-user scenario, we propose an iterative algorithm to maximize the total rates of SCUs for obtaining a suboptimal solution by an alternating iteration manner, where the sum of multiple-ratio fractional programming problem is converted into a convex semidefinite program (SDP) problem. Simulation results show that the proposed algorithm significantly improves the achieved transmission rates of SCUs compared to the case without the IRS.

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Intelligent Reflecting Surface Aided Multi-Antenna Secure Transmission

Cited by 246 publications

References 19 publications

Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead

Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead

Smart and Secure Wireless Communications via Reflecting Intelligent Surfaces: A Short Survey

Resource Allocation for Intelligent Reflecting Surface Enabled Heterogeneous Networks

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