Intelligent Reflecting Surface: A Programmable Wireless Environment for Physical Layer Security
Intelligent Reflecting Surface: A Programmable Wireless Environment for Physical Layer Security
复制标题
智能反射表面：用于物理层安全的可编程无线环境
DOI：
10.1109/access.2019.2924034
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发表时间：
2019-01-01
期刊：
影响因子：
3.9
通讯作者：
Guo, Huayan
中科院分区：
文献类型：
--
作者：
Chen, Jie;Liang, Ying-Chang;Guo, Huayan
在本文中，我们介绍了一个智能反射表面（IRS）提供一个可编程的无线环境的物理层安全。通过调整反射系数，IRS可以改变入射电磁波的衰减和散射，使得它可以以期望的方式朝向预期的接收器传播。具体来说，我们考虑一个下行链路多输入单输出（MISO）广播系统，其中的基站（BS）发送独立的数据流到多个合法的接收器，并保持他们的秘密从多个窃听者。通过联合优化的波束形成器在BS和反射系数在IRS，我们制定了一个最小的保密率最大化问题的反射系数的各种实际约束下。约束条件捕获了反射元件的连续和离散反射系数的情况。由于制定的问题的非凸性，我们提出了一个有效的算法交替优化和路径跟踪算法的基础上，以迭代的方式来解决它。此外，我们证明了该算法可以收敛到局部（全局）最优。此外，我们开发了两个次优算法与某些形式的封闭形式的解决方案，以减少计算复杂度。最后，仿真结果验证了所引入的IRS的优点和所提出的算法的有效性。
In this paper, we introduce an intelligent reflecting surface (IRS) to provide a programmable wireless environment for physical layer security. By adjusting the reflecting coefficients, the IRS can change the attenuation and scattering of the incident electromagnetic wave so that it can propagate in the desired way toward the intended receiver. Specifically, we consider a downlink multiple-input single-output (MISO) broadcast system, where the base station (BS) transmits independent data streams to multiple legitimate receivers and keeps them secret from multiple eavesdroppers. By jointly optimizing the beamformers at the BS and reflecting coefficients at the IRS, we formulate a minimum-secrecy-rate maximization problem under various practical constraints on the reflecting coefficients. The constraints capture the scenarios of both continuous and discrete reflecting coefficients of the reflecting elements. Due to the non-convexity of the formulated problem, we propose an efficient algorithm based on the alternating optimization and the path-following algorithm to solve it in an iterative manner. Besides, we show that the proposed algorithm can converge to a local (global) optimum. Furthermore, we develop two suboptimal algorithms with some forms of closed-form solutions to reduce computational complexity. Finally, the simulation results validate the advantages of the introduced IRS and the effectiveness of the proposed algorithms.