Robust Transmission Design for RIS-Assisted Secure Multiuser Communication Systems in the Presence of Hardware Impairments

被引:14
|
作者
Peng, Zhangjie [1 ,2 ,3 ]
Weng, Ruisong [1 ]
Pan, Cunhua [2 ]
Zhou, Gui [4 ]
Di Renzo, Marco [5 ]
Swindlehurst, A. Lee [6 ]
机构
[1] Shanghai Normal Univ, Coll Informat Mech & Elect Engn, Shanghai 200234, Peoples R China
[2] Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
[3] Shanghai Normal Univ, Shanghai Engn Res Ctr Intelligent Educ & Bigdata, Shanghai 200234, Peoples R China
[4] Friedrich Alexander Univ Erlangen Nurnberg FAU, Inst Digital Commun, D-91054 Erlangen, Germany
[5] Univ Paris Saclay, CNRS, Cent Supelec, Lab Signaux & Syst, F-91192 Gif Sur Yvette, France
[6] Univ Calif Irvine, Dept Elect Engn & Comp Sci, Irvine, CA 92697 USA
基金
欧盟地平线“2020”; 美国国家科学基金会; 上海市自然科学基金; 中国国家自然科学基金;
关键词
Intelligent reflecting surface (IRS); reconfigurable intelligent surface (RIS); hardware impairments (HIs); physical layer security (PLS); INTELLIGENT REFLECTING SURFACE; MASSIVE MIMO SYSTEMS; WIRELESS COMMUNICATION; BEAMFORMING OPTIMIZATION; SECRECY COMMUNICATION; PERFORMANCE ANALYSIS; CHANNEL ESTIMATION; NETWORK; SMART; MODEL;
D O I
10.1109/TWC.2023.3252046
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
This paper investigates reconfigurable intelligent surface (RIS)-assisted secure multiuser communication systems in the presence of hardware impairments (HIs) at the RIS and the transceivers. We jointly optimize the beamforming vectors at the base station (BS) and the phase shifts of the reflecting elements at the RIS so as to maximize the weighted minimum approximate ergodic secrecy rate (WMAESR), subject to the transmission power constraints at the BS and unit-modulus constraints at the RIS. To solve the formulated optimization problem, we first decouple it into two tractable subproblems and then use the block coordinate descent (BCD) method to alternately optimize the subproblems. Two different methods are proposed to solve the two obtained subproblems. The first method transforms each subproblem into a second order cone programming (SOCP) problem by invoking the penalty convex-concave procedure (CCP) method and the closed-form fractional programming (FP) criterion, and then directly solves them by using CVX. The second method leverages the minorization-maximization (MM) algorithm. Specifically, we first derive a concave approximation function, which is a lower bound of the original objective function, and then the two subproblems are transformed into two simple surrogate problems that admit closed-form solutions. Simulation results verify the performance gains of the proposed robust transmission methods over existing non-robust designs. In addition, the MM algorithm is shown to have much lower complexity than the SOCP-based algorithm.
引用
收藏
页码:7506 / 7521
页数:16
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