Abstract
With the development of 5th-generation(5G) wireless systems and internet of things(IoT), high speed wireless communications are facing severe challenges due to numerous connections of communication terminals and limited frequency resources. Intelligent reflecting surface(IRS), a newly appeared wireless communication technology, has attracts people's attentions worldwide by its low power consumptions and costs. In order to improve the communication rates of users, this paper proposes a novel optimization algorithm by implementing the deep learning to IRS for establishing the mapping from the channel state information to the optimal reflecting coefficient matrix of IRS. The present algorithm can perform real-time reconfiguration of IRS while protecting the privacy of IoT users.
Highlights
IEEE Access, 2019(7) : 116753⁃116773 [ 5] RENZO M D, DEBBAH M, PHAN⁃HUY D, et al Smart radio environments empowered by reconfigurable AI meta⁃surfaces: an idea whose time has come[ J]
电信快报, 2020(7) : 8⁃13 YAO Jianwen, WANG Nan. Intelligent reflecting surface: a promising technique for 6G[ J]
Summary
1.1 IRS 的工作原理 IRS 的基本工作原理如图 1 所示,当用户受到 为 M。 因此,从发射机到 IRS 的信道为 HT,m,第 k 个 阵,即 Φkm = diag[ ψ1,ψ2,...,ψ N] ,描述了 IRS 的每个 设 IRS 上具备信道感知能力的激活单元数为 N^ ,且满足 N^ ≪ N。 激活单元可以在 2 种工作模式下
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