智能反射面辅助无线通信系统的信道估计算法设计

Channel Estimation Algorithm Design for Intelligent Reflecting Surface Assisted Wireless Communication System

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。

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.