RIS辅助毫米波系统中基于压缩感知的信道估计

针对可重构智能超表面（RIS）辅助无线通信系统中使用传统信道估计方法导频开销过高的问题，提出了一种基于块稀疏的正交匹配追踪（OMP）信道估计方案。首先，根据毫米波（mmWave）信道模型推导出级联信道矩阵，并将其转换到虚拟角域（VAD）中以获得级联信道的稀疏表示；其次，利用级联信道特有的稀疏特性将信道估计问题转换成稀疏矩阵恢复问题，并使用压缩感知的重构算法进行稀疏矩阵的恢复；最后，通过分析特殊的行-块稀疏结构，对传统的OMP方案进行优化，从而进一步减少导频开销并提升估计性能。仿真结果表明，与传统的OMP方案相比，所提出的基于行-块稀疏结构的优化OMP方案的归一化均方误差（NMSE）减小了大约1 dB。可见，所提出的信道估计方案能够有效减少导频开销并获得更好的估计性能。

Channel estimation based on compressive sensing in RIS-assisted millimeter wave system

Since the pilot overhead using traditional channel estimation methods in the Reconfigurable Intelligent Surface （RIS）-assisted wireless communication systems is excessively high， a block sparseness based Orthogonal Matching Pursuit （OMP） channel estimation scheme was proposed. Firstly， according to the millimeter Wave （mmWave） channel model， the cascaded channel matrix was derived and transformed into the Virtual Angular Domain （VAD） to obtain the sparse representation of the cascaded channels. Secondly， by utilizing the sparse characteristics of the cascaded channels， the channel estimation problem was transformed into the sparse matrix recovery problem， and the reconstruction algorithm based on compressive sensing was adopted to recover the sparse matrix. Finally， the special row-block sparse structure was analyzed， and the traditional OMP scheme was optimized to further reduce pilot overhead and improve estimation performance. Simulation results show that the Normalized Mean Squared Error （NMSE） of the proposed optimized OMP scheme based on the row-block sparse structure decreases about 1 dB compared with that of the conventional OMP scheme. Therefore， the proposed channel estimation scheme can effectively reduce pilot overhead and obtain better estimation performance.