Robust IRS-Aided Secrecy Transmission With Location Optimization

被引:10
|
作者
Bai, Jiale [1 ,2 ]
Wang, Hui-Ming [1 ,2 ]
Liu, Peng [3 ]
机构
[1] Xi An Jiao Tong Univ, Sch Informat & Commun Engn, Xian 710049, Peoples R China
[2] Xi An Jiao Tong Univ, Minist Educ, Key Lab Intelligent Networks & Network Secur, Xian 710049, Peoples R China
[3] Huawei Technol, Wireless Technol Lab, Labs 2012, Shenzhen 518129, Peoples R China
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
Artificial intelligence; Optimization; Probability; Wireless communication; Power system reliability; MISO communication; Communication system security; Physical layer security; intelligent reflecting surface; secrecy rate; location optimization; INTELLIGENT REFLECTING SURFACE; SECURE MIMO TRANSMISSION; WIRELESS COMMUNICATIONS; COMMUNICATION; INFORMATION; ALLOCATION; EXTENSION; FRAMEWORK;
D O I
10.1109/TCOMM.2022.3193404
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this paper, we propose a robust secrecy transmission scheme for intelligent reflecting surface (IRS) aided communication systems. Different from all the existing works where IRS has already been deployed at a fixed location, we take the location of IRS as a variable to maximize the secrecy rate (SR) under the outage probability constraint by jointly optimizing the location of IRS, transmit beamformer and IRS phase shifts with imperfect channel state information (CSI) of Eve, where we consider two cases: a) the location of Eve is known; b) only a suspicious area of Eve is available. We show a critical observation that CSI models are different before and after IRS deployment, thus the optimization problem could be decomposed and solved via a two-stage framework. For case a), in the first stage, universal upper bounds of outage probabilities only related to the location of IRS are derived which can be optimized via successive convex approximation (SCA) method. In the second stage, we develop an alternative optimization (AO) algorithm to optimize beamformer and phase shifts iteratively. For case b), we propose a Max-Min SR scheme based on two-stage framework, where the location of IRS is optimized based on the worst location of Eve. Simulation results indicate the importance of the location of IRS optimization.
引用
收藏
页码:6149 / 6163
页数:15
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