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Intelligent and Converged Networks 2022, 3(1): 119-133 https://doi.org/10.23919/ICN.2021.0020
Open Access | Issue | Published: 30 March 2022

Aerial intelligent reflecting surface for secure wireless networks: Secrecy capacity and optimal trajectory strategy

Show Author's Information Hehao Niu1( ),  Zheng Chu2,  Zhengyu Zhu3,  Fuhui Zhou4
Institute of Electronic Countermeasure, National University of Defense Technology, Hefei 230037, China
Institute for Communication Systems, University of Surrey, Guildford, GU2 7XH, UK, and also with Shaanxi Key Laboratory of Information Communication Network and Security, Xi’an University of Posts & Telecommunications, Xi’an 710121, China
School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China
College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, and also with the Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, Nanjing University of Aeronautics and Astronautics, Nanjing 210000, China
Keywords:
unmanned aerial vehicle (UAV), aerial intelligent reflecting surface (AIRS), alternating optimization, Riemannian manifold optimization (RMO), element-wise block coordinate descent (EBCD)
Cite this article:
Niu H, Chu Z, Zhu Z, et al. Aerial intelligent reflecting surface for secure wireless networks: Secrecy capacity and optimal trajectory strategy . Intelligent and Converged Networks, 2022, 3(1): 119-133. https://doi.org/10.23919/ICN.2021.0020
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Abstract Full text About this article

This work investigates the potential of the aerial intelligent reflecting surface (AIRS) in secure communication, where an intelligent reflecting surface (IRS) carried by an unmanned aerial vehicle (UAV) is utilized to help the communication between the ground nodes. Specifically, we formulate the joint design of the AIRS’s deployment and the phase shift to maximize the secrecy rate. To solve the non-convex objective, we develop an alternating optimization (AO) approach, where the phase shift optimization is solved by the Riemannian manifold optimization (RMO) method, while the deployment optimization is handled by the successive convex approximation (SCA) technique. Furthermore, to reduce the computational complexity of the RMO method, an element-wise block coordinate descent (EBCD) based method is employed. Simulation results verify the effect of AIRS in improving the communication security, as well as the importance of designing the deployment and phase shift properly.


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About this article

Aerial intelligent reflecting surface for secure wireless networks: Secrecy capacity and optimal trajectory strategy

Show Author's information Hehao Niu1( ), Zheng Chu2, Zhengyu Zhu3, Fuhui Zhou4
Institute of Electronic Countermeasure, National University of Defense Technology, Hefei 230037, China
Institute for Communication Systems, University of Surrey, Guildford, GU2 7XH, UK, and also with Shaanxi Key Laboratory of Information Communication Network and Security, Xi’an University of Posts & Telecommunications, Xi’an 710121, China
School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China
College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, and also with the Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, Nanjing University of Aeronautics and Astronautics, Nanjing 210000, China

Abstract

This work investigates the potential of the aerial intelligent reflecting surface (AIRS) in secure communication, where an intelligent reflecting surface (IRS) carried by an unmanned aerial vehicle (UAV) is utilized to help the communication between the ground nodes. Specifically, we formulate the joint design of the AIRS’s deployment and the phase shift to maximize the secrecy rate. To solve the non-convex objective, we develop an alternating optimization (AO) approach, where the phase shift optimization is solved by the Riemannian manifold optimization (RMO) method, while the deployment optimization is handled by the successive convex approximation (SCA) technique. Furthermore, to reduce the computational complexity of the RMO method, an element-wise block coordinate descent (EBCD) based method is employed. Simulation results verify the effect of AIRS in improving the communication security, as well as the importance of designing the deployment and phase shift properly.

Keywords: unmanned aerial vehicle (UAV), aerial intelligent reflecting surface (AIRS), alternating optimization, Riemannian manifold optimization (RMO), element-wise block coordinate descent (EBCD)

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Published: 30 March 2022
Issue date: March 2022

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© All articles included in the journal are copyrighted to the ITU and TUP.

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Acknowledgment

This work was supported in part by the National Natural Science Foundation of China (Nos. 61901490, 61801434, 62071223, and 62031012), the Open Fund of the Shaanxi Key Laboratory of Information Communication Network and Security (No. ICNS201801), the Project funded by China Postdoctoral Science Foundation (No. 2020M682345), and the Henan Postdoctoral Foundation (No. 202001015).

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