论文标题
训练信号设计，用于稀疏渠道估计智能反映表面辅助毫米波通信
Training Signal Design for Sparse Channel Estimation in Intelligent Reflecting Surface-Assisted Millimeter-Wave Communication
论文作者
论文摘要
在本文中，考虑了在稀疏通道模型下进行智能反射表面（IRS）辅助毫米波（MMWAVE）通信的训练信号设计的问题。该问题是根据CRAM $ \急性{\ text {e}} $ r-rao下限（CRB）在通道估计的均方误差（MSE）上解决的。通过利用MMWave通道的稀疏结构，在贝叶斯和混合参数假设下以封闭形式得出了由路径收益和路径角组成的通道参数的CRB。基于推导和分析，提出了一种IRS反射模式设计方法，通过将CRB最小化为设计变量在反射系数上的恒定模量约束下的函数。数值结果验证了稀疏MMWAVE通道估计提出的设计方法的有效性。
In this paper, the problem of training signal design for intelligent reflecting surface (IRS)-assisted millimeter-wave (mmWave) communication under a sparse channel model is considered. The problem is approached based on the Cram$\acute{\text{e}}$r-Rao lower bound (CRB) on the mean-square error (MSE) of channel estimation. By exploiting the sparse structure of mmWave channels, the CRB for the channel parameter composed of path gains and path angles is derived in closed form under Bayesian and hybrid parameter assumptions. Based on the derivation and analysis, an IRS reflection pattern design method is proposed by minimizing the CRB as a function of design variables under constant modulus constraint on reflection coefficients. Numerical results validate the effectiveness of the proposed design method for sparse mmWave channel estimation.
