Adaptive compressed spectrum sensing based on optimized measurement matrix

Wei-gang WANG; Zhen YANG; Bin GU; Hai-feng HU

doi:10.3969/j.issn.1000-436x.2014.08.005

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Adaptive compressed spectrum sensing based on optimized measurement matrix

Academic paper | 更新时间：2024-10-11

- Adaptive compressed spectrum sensing based on optimized measurement matrix
- Journal on Communications Vol. 35, Issue 8, Pages: 33-39(2014)
- 作者机构：
  
  1. 南京邮电大学教育部宽带无线通信和传感网技术重点实验室，江苏南京 210003
  2. 南京邮电大学电子科学与工程学院，江苏南京 210003
  3. 东南大学移动通信国家重点实验室，江苏南京 210008)
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.1000-436x.2014.08.005
  CLC： TN92
- Online First：2014-08，
  
  Published：25 August 2014
- 稿件说明：
移动端阅览
Wei-gang WANG, Zhen YANG, Bin GU, et al. Adaptive compressed spectrum sensing based on optimized measurement matrix[J]. Journal on Communications, 2014, 35(8): 33-39.
DOI：

Wei-gang WANG, Zhen YANG, Bin GU, et al. Adaptive compressed spectrum sensing based on optimized measurement matrix[J]. Journal on Communications, 2014, 35(8): 33-39. DOI： 10.3969/j.issn.1000-436x.2014.08.005.

摘要

推导了自适应压缩感知中的重构估算误差，研究了如何降低观测矩阵列向量之间的自相关性，分析了观测矩阵优化对压缩感知重构算法的影响。将观测矩阵优化与压缩感知自适应过程相结合，提出了基于观测矩阵优化的自适应压缩频谱感知算法。仿真结果证实，所提算法比传统算法重构时产生的均方误差(MSE)更低，在同一观测次数下检测概率更高，在达到同等接收操作性能(ROC)时所需观测次数更少。

Abstract

The estimation error of reconstruction by adaptive compressed sensing was derived

and the column vector autocorrelation of the observation matrix was reduced

and the impact of optimization process on compressed sensing re-construction algorithm was analyzed. Combining the observation matrix optimization and adaptive process

the spectrum sensing algorithm of optimized adaptive compression based on observation matrix was proposed. The simulation results show that the mean square error (MSE) of proposed algorithm is lower than traditional algorithm

and the probability of detection of proposed algorithm is higher on the same number of observations

and the required number of observations is fewer when achieving the same receiver operating performance (ROC).

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references

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