智能反射面辅助太赫兹通信波束赋形与优化技术研究

挖掘太赫兹频段频谱资源是第六代移动通信系统扩容的有效途径，而可靠高效的太赫兹通信需利用智能反射面调整电磁传播环境得以实现。为解决智能反射面辅助太赫兹通信架构中因收发两端阵列规模大、无源智能反射面无独立收发功能带来的硬件复杂度高、信道估计开销大等问题，本项目拟通过 ①研究具有解析结构的低硬件复杂度码本生成方法；②开发具有自适应传输信噪比的波束训练算法；③设计波束赋形中的功率、频谱与反射阵列多维资源分配方案；④构建基于稀疏贝叶斯学习的用户移动特性预测与基于模糊控制原理的波束动态切换机制，为太赫兹通信系统高性能、低复杂度波束赋形的设计与优化提供整套解决方案。研究成果将为智能反射面辅助太赫兹通信系统的设计提供参考依据和理论支持，丰富第六代移动通信系统研发的基础理论与关键技术。因而，本课题研究内容具有重要的理论研究价值，其预期成果将具有实际应用前景。

Terahertz (THz) transmission has been envisioned as a promising candidate for the sixth generation mobile communications (6G) owing to its abundant spectrum resource. Indeed, the reliable and efficient THz transmission can be achieved by employing intelligent reflecting surface (IRS), which can reconfigure propagation environment. However, high complexity on hardware and heavy overhead on channel estimation will occur due to large-scale array and passive elements equipped on IRS. To address these issues, we propose a series of high-performance and low-complexity beamforming solutions for THz communication systems, which follows as: an analytical codebook generation method being of low-hardware-complexity; a beam training algorithm being adaptive to transmission SNR (signal-to-noise ratio); power, spectrum and IRSs multidimensional resource allocation scheme for THz beamforming; user-mobility prediction based on sparse Bayesian learning and beam switch mechanism employing Fuzzy control method. The research results will provide reference basis and theoretical support for the design of the IRS-assisted THz communications, enriching the fundamental theory and key technologies for 6G communications. Thus, our proposal is amazing in the view of both theoretical research and engineering applications.