Wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization

Yuzhi YAN; Youming LI; Guili ZHOU; Yaohui WU

doi:10.11959/j.issn.1000-0801.2016259

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Wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization

research and development | 更新时间：2024-06-05

- Wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization
- Telecommunications Science Vol. 32, Issue 11, Pages: 71-76(2016)
- 作者机构：
  
  1. 宁波大学通信技术研究所，浙江宁波 315211
  2. 浙江万里学院电子信息学院，浙江宁波 315100
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2016259
  CLC： TN929
- Published Online：2016-11，
  
  Published：20 November 2016
- 稿件说明：
移动端阅览
Yuzhi YAN, Youming LI, Guili ZHOU, et al. Wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization[J]. Telecommunications science, 2016, 32(11): 71-76.
DOI：

Yuzhi YAN, Youming LI, Guili ZHOU, et al. Wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization[J]. Telecommunications science, 2016, 32(11): 71-76. DOI： 10.11959/j.issn.1000-0801.2016259.

摘要

宽带分布式协作压缩频谱感知不仅降低过高的采样速率，而且改善在低信噪比环境下的频谱感知性能。为进一步提高频谱感知性能，提出一种基于加权一致优化的宽带分布式协作压缩频谱感知算法。该算法根据当前迭代重构出的频谱信号设定下一次迭代重构的权值，促使频谱信号上存在授权用户的子频段产生信号值，降低重构出错的可能性。仿真结果表明，该算法不仅能够增大频谱重构的准确性，而且能够降低感知过程的时间和通信开销，改善频谱感知性能。

Abstract

Wideband distributed cooperative spectrum sensing based on compressed sensing can not only reduce high sampling rate

but also improve the spectrum sensing performance in low signal to noise ratio environment.In order to further enhance the spectrum sensing performance

a wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization was proposed.In this algorithm

the next iterative reconstruction weights were determined according to the current iterative reconstructed spectrum signal

which can encourage the sub-band occupied by primary user to generate signal value and decrease the likelihood of incorrect reconstruction.Simulation results show that the proposed algorithm can not only increases the spectral reconstruction accuracy

but also reduces time and communication costs of the sensing process

and improves the spectrum sensing performance.

关键词

Keywords

references

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