压缩感知理论在IR-UWB系统信道估计中的应用

Application of the Compressed Sensing Theory in the IR-UWB System Channel Estimation

采用压缩感知理论实现IR-UWB超宽带无线通信系统的信道估计。首先介绍压缩感知理论的稀疏信号、观测矩阵和重构算法。其次论述IR-UWB无线通信系统的组成,UWB多径信道采用IEEE 802.15.SG3a信道模型。根据循环卷积的矩阵计算方法,推导出IR-UWB系统信道估计的压缩感知模型,采用GOMP算法实现对IR-UWB系统信道参数的重构。借助Matlab软件,搭建了IR-UWB系统信道估计的仿真实验平台,编写M脚本程序,实现了LS算法和GOMP算法对IR-UWB系统信道参数的估计。仿真实验结果表明,GOMP算法能够很好地重构IR-UWB系统信道参数。通过比较NMSE,能够看出GOMP算法重构的精度高于LS算法。

The channel estimation of the IR-UWB UWB wireless communication system is solved by the compressed sensing theory.First,the paper introduces sparse signals,observation matrices,and reconstruction algorithms for compressed sensing theory.Secondly,the structure of UWB-IR wireless communication system is discussed,the IEEE 802.15.SG3a channel model is used as the UWB multipath channel.According to the matrix calculation method of the cyclic convolution,the compressed sensing model of channel estimation in the IR-UWB system is deduced,the channel parameters of the IRUWB system are reconstructed by the GOMP algorithm.The simulation experiment platform of the IR-UWB system channel estimation is designed by the MATLAB software,by designing the M script program,the channel parameters of the IR-UWB system are estimated by the LS algorithm and the GOMP algorithm.The experimental results show that the channel parameters of the IR-UWB system can be reconstructed well by the GOMP algorithm.By comparing NMSE,it can be showed that the reconstruction accuracy of the GOMP algorithm is higher than that of LS algorithm.