基于TM基的压缩感知无线信道估计测量矩阵的构造  

Construction of Measurement Matrix for Compressed Sensing Wireless Channel Estimation Based on TM

作　　者：钱婷 雷娅 

机构地区：[1]上海电子工业学校,上海200240 [2]招银网络科技(杭州)有限公司,浙江杭州310051

出　　处：《工业控制计算机》2020年第10期65-66,105,共3页Industrial Control Computer

摘　　要：使用压缩感知方法可以实现无线信道的有效估计,测量矩阵的选取是压缩感知信道估计中一个关键问题,直接影响到信道估计的效果。目前常用的一些测量矩阵如随机高斯矩阵在基于Takenaka-Malmquist基函数的压缩感知信道估计中效果并不理想。使用有效投影来优化测量矩阵,从多维尺度分解的角度设计一个新的测量矩阵。仿真结果说明了该测量矩阵在基于Takenaka-Malmquist基函数的压缩感知信道估计的有效性。Effective estimation of wireless channels can be realized by using compression sensing methods,and the selection of measurement matrix is a key issue in compressed sensing channel estimation,which directly affects the effect of channel estimation.However,some commonly used measurement matrices such as random Gaussian matrices do not work well in the estimation of compressed sensing channel estimation based on Takenaka-Malmquist basis functions.This paper uses effective projections to optimize the measurement matrix and designs a new measurement matrix from the perspective of a multidimensional scale decomposition.The simulation result shows the effectiveness of the measurement matrix in compressed sensing channel estimation based on the Takenaka-Malmquist basic function.

关 键 词：压缩感知 信道估计 测量矩阵 Takenaka-Malmquist基函数 

分 类 号：TN92[电子电信—通信与信息系统]