电子科技大学学报2017，Vol.46Issue(3)：498-504,7.DOI:10.3969/j.issn.1001-0548.2017.03.004
一种稀疏度自适应超宽带信道估计算法
Sparsity Adaptive Algorithm for Ultra-Wideband Channel Estimation
摘要
Abstract
Ultra-wideband (UWB) channel estimation based on the theory of compressive sensing needs to predict sparsity of the channel.Considering the sparseness of the UWB channel in time domain,the problem of channel estimation can be transformed into the reconstruction of the sparse vector in compressive sensing theory.Sparsity adaptive regularization compressive sampling matching pursuit (SARCoSaMP) algorithm is proposed in this paper.The ideas of adaptive and regularization are introduced based on compressive sampling matching pursuit (CoSaMP) algorithm.The number of the selected atoms is controlled automatically in order to approach channel sparsity K gradually.The UWB channel is estimated accurately although the sparsity of the channel is not available.Results show that the proposed algorithm can be effectively used in ultra-wideband channel estimation and it is significantly superior to CoSaMP and sparsity adaptive matching pursuit (SAMP) algorithm.关键词
信道估计/压缩感知/稀疏度自适应/超宽带Key words
channel estimation/compressive sensing/sparsity adaptive/ultra-wideband (UWB)分类
信息技术与安全科学引用本文复制引用
王艳芬,丛潇雨,孙彦景..一种稀疏度自适应超宽带信道估计算法[J].电子科技大学学报,2017,46(3):498-504,7.基金项目
国家自然科学基金(51274202) （51274202）
