摘 要：针对智能反射面（IRS）辅助无线通信系统的信道估计问题进行研究。IRS 由大量无源器件组成，自身没有信号处理能力，使得其在 IRS 辅助无线通信系统的信道估计中，消耗较大的导频资源。为了减少导频开销，利用用户间角度域级联信道特有的公共非零行结构的稀疏性，结合稀疏度自适应匹配追踪算法（SAMP），提出了基于 C-SAMP 的信道估计算法。仿真结果表明，所提出的算法相比其他压缩感知算法有效地降低了导频开销，而且在低信噪比条件下，归一化均方误差降低约 1 ～ 2 dB。
关键词：智能反射面；信道估计；压缩感知；稀疏度自适应匹配追踪算法
DOI:10.19850/j.cnki.2096-4706.2023.01.018
基金项目：国家自然科学基金项目（51977001）；安徽省科技人才支持计划（PU19100018）
中图分类号：TN929.5 文献标识码：A 文章编号：2096-4706（2023）01-0068-04
Channel Estimation Algorithm Design for Intelligent Reflecting Surface Assisted Wireless Communication System
LI Yan, LI Cong, XU Zhihao
(School of Electrical and Information Engineering, Anhui University of Technology, Maanshan 243032, China)
Abstract: The channel estimation problem of Intelligent Reflection Surface (IRS) assisted wireless communication system is studied. IRS is composed of a large number of passive components, which has no signal processing capability, so it consumes a large amount of pilot resources in the channel estimation of IRS assisted wireless communication system. In order to reduce pilot cost, a channel estimation algorithm based on C-SAMP is proposed by using the sparsity of common non-zero row structure unique to angle domain cascaded channels between users and combining the sparsity adaptive match pursuit algorithm (SAMP). The simulation results show that the proposed algorithm effectively reduces the pilot cost compared with other compression sensing algorithms, and the normalized mean square error is reduced by about 1～2 dB under the condition of low SNR.
Keywords: intelligent reflecting surface; channel estimation; compressive sensing; SAMP
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作者简介：李岩（1997—），女，汉族，山西临汾人，硕士研究生在读，研究方向：智能反射面技术；李聪（1980—），男，汉族，山西吕梁人，副教授，博士，研究方向：无线通信、光纤通信、高性能纠错码、5G 的物理层算法、人体通信等；徐志豪（1997—），男，汉族，安徽合肥人，硕士研究生，研究方向：智能反射面技术和无线电技术。