电信科学 ›› 2016, Vol. 32 ›› Issue (11): 71-76.doi: 10.11959/j.issn.1000-0801.2016259

• 研究与开发 • 上一篇    下一篇

基于加权一致优化的宽带分布式协作压缩频谱感知算法

闫玉芝1,李有明1,周桂莉1,吴耀辉1,2   

  1. 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
  • 出版日期:2016-11-20 发布日期:2017-06-05
  • 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;宁波市自然科学基金资助项目

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

Yuzhi YAN1,Youming LI1,Guili ZHOU1,Yaohui WU1,2   

  1. 1 Institute of Communication Technology,Ningbo University,Ningbo 315211,China
    2 School of Electronic and Information Engineering,Zhejiang Wanli University,Ningbo 315100,China
  • Online:2016-11-20 Published:2017-06-05
  • Supported by:
    The National Natural Science Foundation of China;Ningbo Natural Science Foundation of China;Ningbo Natural Science Foundation of China

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。

关键词: 宽带频谱感知, 压缩感知, 分布式协作, 加权一致优化

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.

Key words: wideband spectrum sensing, compressed sensing, distributed cooperation, weighted consensus optimization

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