Secure Transmission by Leveraging Multiple Intelligent Reflecting Surfaces in MISO Systems
Secure Transmission by Leveraging Multiple Intelligent Reflecting Surfaces in MISO Systems
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DOI：
10.1109/tmc.2021.3114167
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发表时间：
2020-08
影响因子：
7.9
通讯作者：
Jian Li;Lan Zhang;Kaiping Xue;Yuguang Fang
中科院分区：
文献类型：
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作者：
Jian Li;Lan Zhang;Kaiping Xue;Yuguang Fang
智能反射面（IRS）的最新进展通过重新配置传输环境为安全通信引入了一个新的维度。在本文中，我们设计了一种利用多个协作IRSs的多用户多输入单输出系统的安全传输方案。具体而言，为了保证多个合法用户之间的最坏情况下可实现的保密率，我们制定了一个最大最小问题，该问题可以通过交替优化方法将其解耦为多个子问题来解决。基于半定松弛和逐次凸逼近，每个子问题都可以进一步转化为凸问题，易于求解。大量的实验结果表明，我们提出的方案可以适应多用户的复杂场景，并在可实现的保密率方面取得了显着的提高。与传统的单IRS方案相比，在多用户场景下，随着反射单元数量的增加，该方案在2.4 ~ 6.4 bps/Hz范围内可以获得更好的性能。我们还评估了连续相移/幅度控制和离散相移/幅度控制下的保密率之间的差距，结果表明，随着离散化粒度的增加，离散近似方法获得的保密率收敛于所提出方案的保密率。
Recent advance of Intelligent Reflecting Surface (IRS) introduces a new dimension for secure communications by reconfiguring the transmission environments. In this paper, we devise a secure transmission scheme for multi-user Mutiple-Input Single-Output systems by leveraging multiple collaborative IRSs. Specifically, to guarantee the worst-case achievable secrecy rate among multiple legitimate users, we formulate a max-min problem that can be solved by an alternating optimization method to decouple it into multiple sub-problems. Based on semidefinite relaxation and successive convex approximation, each sub-problem can be further converted into convex problem and easily solved. Extensive experimental results demonstrate that our proposed scheme can adapt to complex scenarios for multiple users and achieve significant gain in terms of achievable secrecy rate. Compared to the traditional single IRS scheme, the proposed scheme can achieve better performance at the range of 2.4-6.4 bps/Hz with the increase in the number of reflecting elements in the multi-user scenarios. We also evaluate the gap between the secrecy rate for our proposed scheme under continuous phase shift/amplitude control and discrete phase shift/amplitude control, and our results show that the secrecy rate obtained from discrete approximation method converges to that achieved from the proposed scheme when increasing the discretization granularity.