Enhancing Secure MIMO Transmission via Intelligent Reflecting Surface

Dong, Limeng; Wang, Huiming

doi:10.1109/twc.2020.3012721

Cited by 151 publications

(55 citation statements)

References 34 publications

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“…In contrast with the multiple-input single-output (MISO) systems, the IRS assisted multiple-input multiple-output (MIMO) systems is more meaningful at high frequency bands [59][60][61], which employs a large number of array antennas to conquer the serious path loss at both transmitter and receiver. For instance, based on the deep reinforcement learning, the post decision state and prioritized experience replay are employed to improve the security performance for the MIMO communication system [62,63]. Through the above discussion, the research on IRS assisted secure communications is still in infancy stage, especially for THz communications.…”

Section: Irs Empowered Secure Thz Communicationsmentioning

confidence: 99%

Towards intelligent reflecting surface empowered 6G terahertz communications: A survey

et al. 2021

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Terahertz (THz) communications have been widely envisioned as a promising enabler to provide adequate bandwidth and achieve ultra-high data rates for sixth generation (6G) wireless networks. In order to mitigate blockage vulnerability caused by serious propagation attenuation and poor diffraction of THz waves, an intelligent reflecting surface (IRS), which manipulates the propagation of incident electromagnetic waves in a programmable manner by adjusting the phase shifts of passive reflecting elements, is proposed to create smart radio environments, improve spectrum efficiency and enhance coverage capability. Firstly, some prospective application scenarios driven by the IRS empowered THz communications are introduced, including wireless mobile communications, secure communications, unmanned aerial vehicle (UAV) scenario, mobile edge computing (MEC) scenario and THz localization scenario. Then, we discuss the enabling technologies employed by the IRS empowered THz system, involving hardware design, channel estimation, capacity optimization, beam control, resource allocation and robustness design. Moreover, the arising challenges and open problems encountered in the future IRS empowered THz communications are also highlighted. Concretely, these emerging problems possibly originate from channel modeling, new material exploration, experimental IRS testbeds and intensive deployment. Ultimately, the combination of THz communications and IRS is capable of accelerating the

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Section: Irs Empowered Secure Thz Communicationsmentioning

confidence: 99%

Towards intelligent reflecting surface empowered 6G terahertz communications: A survey

et al. 2021

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“…Based on the above proposed two iterative algorithms and the initialization of feasible solution, the proposed AO method for solving the joint active and passive beamforming optimization problem is summarized in Algorithm 3, where T max and ξ 3 denote the permitted maximum number of iterations and the threshold of algorithm termination, respectively. In the proposed AO method, the Taylor expansion as shown in (34) is introduced in problem OP3 and problem OP6. In addition, for solving problem OP6, the SROCR method can approximate the optimal rank-one solution from the upper bound by introducing the rank-one relaxation constraint.…”

Section: E Algorithm Analysismentioning

confidence: 99%

“…In [33], the intelligent reflecting surfaces (IRSs) are employed to enhance the physical layer security in a challenging radio environment, where a penalty-based approach is used to obatin the passive beamforming. In [34], the one-by-one (OBO) method is proposed to optimize the passive beamforming, in which each one of the phase coefficents are optimized in order by fixing the other coefficients as constant.…”

mentioning

confidence: 99%

Intelligent Reflecting Surface Aided NOMA for Millimeter-Wave Massive MIMO With Lens Antenna Array

Liu

Cheng

et al. 2021

IEEE Trans. Veh. Technol.

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In this paper, we propose a downlink intelligent reflecting surface (IRS) aided non-orthogonal multiple access (NOMA) for millimeter-wave (mmWave) massive MIMO with lens antenna array, i.e., IRS-aided mmWave beamspace NOMA, where the single-antenna users without direct-link but connected to the base station (BS) with the aid of the IRS are grouped as one NOMA group. Considering the power leakage problem in beamspace channel and the per-antenna power constraint, we propose two multi-beam selection strategies for the BS-IRS link under two channel models, i.e., 2-dimension (2D) channel model and 3-dimension (3D) channel model, respectively, where two corresponding RF chain configuration strategies are designed, respectively. Then, we formulate and solve the optimization problem for maximizing the weighted sum rate by jointly optimizing the active beamforming at the BS and the passive beamforming at the IRS, where we propose the alternating optimization (AO) method to solve the above joint optimization problem. Especially, different from the stochastic method, based on the beam-splitting technique, we propose the method to initialize the feasible solution for the proposed AO method, where the transmit power minimization problem is formulated and solved. Through simulations, the weighted sum rate performance of the proposed IRS-aided mmWave beamspace NOMA is verified.

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“…Different from the conventional relaying and backscatter communications that require power amplifiers to retransmit the signal received, IRS does not process any incident signals but only reflects the incident signals without amplifying or decoding, thus incurring no additional hardware cost and power consumption [5], [6]. Since IRS is not equipped with expensive signal processing equipments such as digital-to-analog converter and modulator/demodulator, IRS is simple and low-cost that can be easily deployed on urban commercial buildings, shopping mall or indoor spaces [6], [7]. These significant advantages make IRS passive beamforming as a green energy-efficient technique for 6G cellular Internet of Things (IoT), and hence it has been investigated in different wireless communication such as multi-cell cellular networks, secure MIMO transmission, simultaneous wireless information and power transfer (SWIPT) etc.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Evolutionary-Based Sparse Channel Estimation for IRS-Assisted mmWave MIMO Systems

Chen

Tang

Zhang

et al. 2022

IEEE Trans. Wireless Commun.

114

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The intelligent reflecting surface (IRS)-assisted millimeter wave (mmWave) communication system has emerged as a promising technology for coverage extension and capacity enhancement. Prior works on IRS have mostly assumed perfect channel state information (CSI), which facilitates in deriving the upper-bound performance but is difficult to realize in practice due to passive elements of IRS without signal processing capabilities. In this paper, we propose a compressive channel estimation techniques for IRS-assisted mmWave multi-input and multi-output (MIMO) system. To reduce the training overhead, the inherent sparsity of mmWave channels is exploited. By utilizing the properties of Kronecker products, IRS-assisted mmWave channel is converted into a sparse signal recovery problem, which involves two competing cost function terms (measurement error and sparsity term). Existing sparse recovery algorithms solve the combined contradictory objectives function using a regularization parameter, which leads to a suboptimal solution. To address this concern, a hybrid multiobjective evolutionary paradigm is developed to solve the sparse recovery problem, which can overcome the difficulty in the choice of regularization parameter value. Simulation results show that under a wide range of simulation settings, the proposed method achieves competitive error performance compared to existing channel estimation methods.

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Enhancing Secure MIMO Transmission via Intelligent Reflecting Surface

Cited by 151 publications

References 34 publications

Towards intelligent reflecting surface empowered 6G terahertz communications: A survey

Towards intelligent reflecting surface empowered 6G terahertz communications: A survey

Intelligent Reflecting Surface Aided NOMA for Millimeter-Wave Massive MIMO With Lens Antenna Array

Hybrid Evolutionary-Based Sparse Channel Estimation for IRS-Assisted mmWave MIMO Systems

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