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适用于无线传感器网络的层次化分布式压缩感知

程银波 司菁菁 候肖兰

程银波, 司菁菁, 候肖兰. 适用于无线传感器网络的层次化分布式压缩感知[J]. 电子与信息学报, 2017, 39(3): 539-545. doi: 10.11999/JEIT160439
引用本文: 程银波, 司菁菁, 候肖兰. 适用于无线传感器网络的层次化分布式压缩感知[J]. 电子与信息学报, 2017, 39(3): 539-545. doi: 10.11999/JEIT160439
CHENG Yinbo, SI Jingjing, HOU Xiaolan. Hierarchical Distributed Compressed Sensing for Wireless Sensor Network[J]. Journal of Electronics & Information Technology, 2017, 39(3): 539-545. doi: 10.11999/JEIT160439
Citation: CHENG Yinbo, SI Jingjing, HOU Xiaolan. Hierarchical Distributed Compressed Sensing for Wireless Sensor Network[J]. Journal of Electronics & Information Technology, 2017, 39(3): 539-545. doi: 10.11999/JEIT160439

适用于无线传感器网络的层次化分布式压缩感知

doi: 10.11999/JEIT160439
基金项目: 

国家自然科学基金(61471313, 61303128),河北省自然科学基金(F2014203183),燕山大学青年教师自主研究计划课题(13LGB015),秦皇岛市科学技术研究与发展计划(201602A031)

Hierarchical Distributed Compressed Sensing for Wireless Sensor Network

Funds: 

The National Natural Science Foundation of China (61471313, 61303128), The Natural Science Foundation of Hebei Province (F2014203183), The Youth Foundation of Yanshan University (13LGB015), The Science and Technology Plan of Qinhuangdao (201602A031)

  • 摘要: 分布式压缩感知(Distributed Compressed Sensing, DCS)是在无线传感器网络(Wireless Sensor Network, WSN)中减少数据传输量、降低能量消耗的有效手段。该文面向分簇WSN,提出层次化分布式压缩感知(Hierarchical Distributed Compressed Sensing, HDCS)。在利用簇内DCS消除簇内时间、空间冗余的基础上,利用簇间DCS消除簇间空间冗余,减少簇头的数据发送量。针对分簇WSN采集信号的结构化稀疏特性,建立块稀疏簇内联合稀疏模型与块稀疏簇间联合稀疏模型,提出HDCS观测方案与层次化联合重构算法。仿真结果表明,与普通DCS相比,HDCS在保证重建信号质量的同时,能够有效减轻簇头的通信负担,并显著降低Sink上的信号重构时间。
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出版历程
  • 收稿日期:  2016-05-03
  • 修回日期:  2016-11-23
  • 刊出日期:  2017-03-19

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