Secrecy Rate Maximization for Intelligent Reflecting Surface Assisted Multi-Antenna Communications

By Hong Shen, Wei Xu, Shulei Gong, Zhenyao He, Chunming Zhao. IEEE Communications Letters, 2019

477 citations recorded by the source corpus.

We investigate transmission optimization for intelligent reflecting surface (IRS) assisted multi-antenna systems from the physical-layer security perspective. The design goal is to maximize the system secrecy rate subject to the source transmit power constraint and the unit modulus constraints imposed on phase shifts at the IRS. To solve this complicated non-convex problem, we develop an efficient alternating algorithm where the solutions to the transmit covariance of the source and the phase shift matrix of the IRS are achieved in closed form and semi-closed form, respectively. The convergence of the proposed algorithm is guaranteed theoretically. Simulation results validate the performance advantage of the proposed optimized design.

View Paper: https://www.semanticscholar.org/paper/c758ab8d38cf4389ed1d4f77620510c763e739c0

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1. Yuanwei Liu
2. Xidong Mu
3. M. Di Renzo
4. Qingqing Wu
5. Rui Zhang
6. Emil Björnson
7. Alessio Zappone
8. Cunhua Pan

Citations in the corpus

• Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks (2019, background): “, wireless power transfer [8], [9], physical layer security [10]–[12], cognitive radio network [13], etc.”
• Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey (2019, background): “This idea has been extended in the recent research works by considering multiple antennas at the LR/eavesdropper [162], [163], rank-one/full-rank communication channels [164], and secure THz communications [165].”
• Intelligent Reflecting Surface Aided MIMO Broadcasting for Simultaneous Wireless Information and Power Transfer (2019, background): “The authors of [16]–[18] studied the security issues of a single-user case, while the authors of [19]–[21] considered multiple-user scenarios.”
• Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement Learning (2020, methodology): “Instead, in general, algorithms are developed to find out suboptimal solutions employing alternating optimization techniques to maximize the objective functions, where in each iteration, suboptimal G is solved by first fixing Φ [15][20] while suboptimal Φ is derived by fixing the G, until the algori”
• Reconfigurable Intelligent Surfaces: Principles and Opportunities (2020, methodology): “Powerful optimization techniques, such as convex optimization [91], iterative algorithm [73], gradient descent approach [79], and alternating algorithm [104] have been adopted for addressing the aforementioned fundamental challenges.”
• Deep Reinforcement Learning-Based Intelligent Reflecting Surface for Secure Wireless Communications (2020, methodology): “in [14] and [15] applied the alternative optimization (AO) algorithm to jointly optimize the transmit beamforming vector at”
• An Overview of Signal Processing Techniques for RIS/IRS-Aided Wireless Systems (2021, unknown): “…such as mmWave/terahertz systems [84], [89], [142]–[145], multicell systems [101], [146], [147], physical layer security systems [83], [87], [88], [97], [98], [148], [149], simultaneous wireless information and power transfer (SWIPT) [99], [108], [113], [150]–[154], mobile edge computing networks…”
• Multi-Hop RIS-Empowered Terahertz Communications: A DRL-Based Hybrid Beamforming Design (2021, methodology): “…installation in building facades, ceilings of training, walls, laptops, clothes, etc., 2) ready integration into existing communication systems without the modifications on hardware, as well as 3) compact deployment of multiple RISs along the signal propagation path [3], [9], [21], [22], [27]–[38].”
• Robust and Secure Wireless Communications via Intelligent Reflecting Surfaces (2019, methodology): “All these existing works [1], [16]–[20] assumed that the potential eavesdroppers are equipped with a single antenna and perfect channel state information (CSI) of the eavesdropping channels is available at the AP.”
• Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead (2020, background): “In [197], the authors study the problem of secrecy rate maximization in an RIS-assisted wiretap channel.”
• Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How it Works, State of Research, and Road Ahead (2020, background): “In [196], the authors study the problem of secrecy rate maximization in an RIS-assisted wiretap channel.”
• Intelligent Reflecting Surface Aided Multigroup Multicast MISO Communication Systems (2019, background): “in [8] derive closed-form transmit covariance matrix of the source and semi-closed-form phase shift matrix of the IRS for the security rate maximization problem.”