[1]刘正其,季薇.一种改进的基于BOMP的宽带频谱感知算法[J].计算机技术与发展,2014,24(06):118-121.
　LIU Zheng-qi,JI Wei.A Modified Spectrum Sensing Algorithm for Wideband Cognitive Radio Based on BOMP[J].,2014,24(06):118-121.
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一种改进的基于BOMP的宽带频谱感知算法()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
24
期数:
2014年06期
页码:
118-121
栏目:
智能、算法、系统工程
出版日期:
2014-06-30

文章信息/Info

Title:
A Modified Spectrum Sensing Algorithm for Wideband Cognitive Radio Based on BOMP
文章编号:
1673-629X（2014）06-0118-04
作者:
刘正其; 季薇
1.南京邮电大学 通信与信息工程学院；2.宽带无线通信与传感网技术教育部重点实验室
Author(s):
LIU Zheng-qi; JI Wei
关键词:
认知无线电; 压缩感知; 宽带; 块稀疏
Keywords:
cognitive radio; compressed sensing; wideband; block-sparse
分类号:
TP301.6
文献标志码:
A
摘要:
块稀疏信号是一种典型的稀疏信号，在块稀疏信号的压缩感知问题中，现有的理论研究往往假设信号的非零子块边界已知，然而这一先验信息对次用户往往是受限的。文中基于块稀疏信号压缩感知理论，研究块稀疏信号在非零子块边界信息未知时的压缩感知重建问题，提出一种融合了传统的单点重构算法和块稀疏重构算法的新算法。该算法将能量检测嵌入到重构算法中，用以判断块的完整性，实现了频谱感知与压缩感知的有机结合，不仅利用信号的块稀疏性提高了频谱检测速度，而且利用单点的OMP提高了算法的准确度。仿真表明，改进算法在非零子块边界信息未知时，依然能在很短的检测耗时下以较低的检测错误概率检测出信道的占用情况。
Abstract:
Block-sparse signal is a typical sparse signal. To deal with the compressed sensing problem of block-sparse signal,most of the existing theories assume that the boundary conditions of non-zero signals are known. However,this priori information is often limited to secondary users. In this paper,try to solve the reconstruction problem of imperfect block sparse signals without the boundary conditions of the non-zero signals. A modified spectrum sensing algorithm for wideband cognitive radio based on block-sparse orthogonal matching pursuit is proposed,which combines traditional single-point reconstruction algorithm and block sparse reconstruction algorithm together. To judge the integrity of the block,energy detection is used in reconstructing,not only improving the spectrum detection speed by the block sparse of signal,but also enhancing the accuracy of the algorithm by OMP. Simulation results show that,the modified algorithm still can detect the occupancy of the channel in a very short time under a low detection error probability without the boundary of the non-zero sub-block.

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更新日期/Last Update: 1900-01-01