计算机应用 ›› 2014, Vol. 34 ›› Issue (9): 2514-2517.DOI: 10.11772/j.issn.1001-9081.2014.09.2514

• 网络与通信 • 上一篇    下一篇

基于一次投影子空间追踪的压缩感知信号重构

刘小青,李有明,李程程,季彪,陈斌,邹婷   

  1. 宁波大学 通信技术研究所,浙江 宁波 315211
  • 收稿日期:2014-04-08 修回日期:2014-06-16 出版日期:2014-09-01 发布日期:2014-09-30
  • 通讯作者: 刘小青
  • 作者简介: 
    刘小青(1991-),男,湖北襄阳人,硕士研究生,主要研究方向:压缩感知、协作通信;
    李有明(1963-),男,陕西扶风人,教授,博士生导师,博士,主要研究方向:压缩感知、协作通信;
    李程程(1991-),男,安徽淮南人,硕士研究生,主要研究方向:压缩感知、信道估计;
    季彪(1989-),男,安徽宿州人,硕士研究生,主要研究方向:压缩感知、水声通信;
    陈斌(1989-),男,浙江临安人,硕士研究生,主要研究方向:协作通信资源分配;
    邹婷(1989-),女,浙江衢州人,硕士研究生,主要研究方向:电力线通信系统。
  • 基金资助:

    国家自然科学基金资助项目;宁波市自然科学基金资助项目;宁波市科技创新团队项目;校级研究生科研创新基金资助项目

One projection subspace pursuit for signal reconstruction in compressed sensing

LIU Xiaoqing,LI Youming,LI Chengcheng,JI Biao,CHEN Bin,ZHOU Ting   

  1. Institute of Communication Technology, Ningbo University, Ningbo Zhejiang 315211, China
  • Received:2014-04-08 Revised:2014-06-16 Online:2014-09-01 Published:2014-09-30
  • Contact: LIU Xiaoqing

摘要:

为了降低信号重构算法的复杂度,实现对稀疏度未知信号的重构,提出了一种基于一次投影子空间追踪(OPSP)的信号重构方法。首先根据约束等距性质确定信号稀疏度的上下界,并将最接近上下界中值的整数作为稀疏度的估计值;然后在子空间追踪(SP)算法的框架下,去掉了迭代中观测向量在支撑集上的投影过程,降低了算法的复杂度。为了更准确地衡量算法的重构性能,提出用完整信号的重构概率作为衡量算法重构性能的指标。与传统的SP算法相比,所提算法可以重构稀疏度未知的信号,且重构时间短,重构概率高。仿真结果验证了该算法的有效性。

Abstract:

In order to reduce the complexity of signal reconstruction algorithm, and reconstruct the signal with unknown sparsity, a new algorithm named One Projection Subspace Pursuit (OPSP) was proposed. Firstly, the upper and lower bounds of the signal's sparsity were determined based on the restricted isometry property, and the signal's sparsity was set as their integer middle value. Secondly, under the frame of Subspace Pursuit (SP), the projection of the observation onto the support set in each iteration process was removed to decrease the computational complexity of the algorithm. Furthermore, the whole signal's reconstruction rate was used as the index of reconstruction performance. The simulation results show that the proposed algorithm can reconstruct the signals of unknown sparsity with less time and higher reconstruction rate compared with the traditional SP algorithm, and it is effective for signal reconstruction.

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