压缩感知在稀疏信道估计中的应用  

Application of Compressive Sensing Theory in Sparse Channel Estimation

作　　者：何雪云[1] 潘林[2] 彭伟刚[3] 

机构地区：[1]南京邮电大学通信与信息工程学院,江苏南京210003 [2]解放军理工大学指挥自动化学院,江苏南京210007 [3]中国移动通信集团江苏有限公司,江苏南京210029

出　　处：《通信技术》2011年第9期27-29,共3页Communications Technology

摘　　要：压缩感知(CS,Compressive Sensing)理论指出可以用低于奈奎斯特抽样定理的速率对稀疏信号进行采样并在收端以很高的概率重建信号,它是目前信号处理领域的研究热点。基于CS理论的信道估计会降低导频辅助信道估计的导频数量且估计性能好,介绍了CS的基本原理和信道估计相关内容,以及正交频分复用(OFDM,Orthogonal Frequency Division Multiplex)系统和UWB系统中2种不同的基于CS的信道估计方法,重点是基于CS的信道估计的数学建模过程。Recently,compressive sensing（CS） technology is a hot research topic in signal processing area,this technology could sample the sparse signal at a rate much lower than Nyquist rate and reconstruct it with high probability by optimization technique.CS-based channel estimation could reduce the number of pilot symbols and has a better estimation performance as compared with traditional channel estimation.Two different CS-based channel estimations in orthogonal frequency division multiplex（OFDM） system and ultra wideband（UWB） system are described in this paper,with emphasis on mathematical modeling of these two CS-base channel estimations.

关 键 词：压缩感知 稀疏信道估计 正交频分复用 超宽带系统 

分 类 号：TN911.23[电子电信—通信与信息系统]