Ultrawideband Channel Estimation: A Bayesian Compressive Sensing Strategy Based on Statistical Sparsity
Ultrawideband Channel Estimation: A Bayesian Compressive Sensing Strategy Based on Statistical Sparsity
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超宽带信道估计：基于统计稀疏性的贝叶斯压缩感知策略
DOI：
10.1109/tvt.2014.2340894
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发表时间：
2015-05
期刊：
影响因子：
--
通讯作者：
Yong Liang Guan
中科院分区：
文献类型：
--
作者：
Xiantao Cheng;Mengyao Wang;Yong Liang Guan
To cope with the formidable sampling rate required by Nyquist criterion, compressive sensing (CS) has been recently adopted for ultrawideband (UWB) channel estimation. In this paper, exploiting the statistical sparsity of real UWB signals in the basis formed by eigenvectors, we develop a new CS dictionary called eigendictionary, which enables the use of CS for UWB channel estimation. With respect to the eigendictionary, the expansion vector of UWB signals is sparse and exhibits an additional structure in the form of statistically significant coefficients occurring in clusters. Capitalizing on this structure, we propose two novel Bayesian CS (BCS) algorithms to efficiently reconstruct UWB signals from a small collection of random projection measurements. Furthermore, by utilizing the common sparsity profile inherent in UWB signals, we extend the proposed Bayesian algorithms to multitask (MT) versions, which can simultaneously recover multiple UWB signals if available. Since the statistical connection between different UWB signals is exploited, the developed MT-BCS can obtain better performance than the single-task version. Extensive simulations using real UWB data show that the proposed schemes considerably reduce the requirement on sampling rate and present excellent performance compared with the traditional correlator and other CS-based channel estimation schemes.
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影响因子：
6.8
作者：
Keith Q. T. Zhang;S. H. Song
通讯作者：
Keith Q. T. Zhang;S. H. Song
DOI：
10.1017/cbo9780511794308
发表时间：
2012
期刊：
--
影响因子：
--
作者：
Gitta Kutyniok
通讯作者：
Gitta Kutyniok
DOI：
10.1109/spawc.2007.4401384
发表时间：
2007-06
期刊：
2007 IEEE 8th Workshop on Signal Processing Advances in Wireless Communications
影响因子：
--
作者：
Zhongmin Wang;Gonzalo R. Arce;J. Paredes;Brian M. Sadler
通讯作者：
Zhongmin Wang;Gonzalo R. Arce;J. Paredes;Brian M. Sadler
影响因子：
5.4
作者：
Ji, Shihao;Dunson, David;Carin, Lawrence
通讯作者：
Carin, Lawrence
DOI：
10.1109/glocom.2012.6503753
发表时间：
2012-12
期刊：
--
影响因子：
--
作者：
Xiantao Cheng;Y. Guan;Guangrong Yue;Shaoqian Li
通讯作者：
Xiantao Cheng;Y. Guan;Guangrong Yue;Shaoqian Li