Compressed sensing algorithm based on data fusion tree in wireless sensor networks

被引：0
作者：
Huang, Hai-Ping [1 ,2 ]
Chen, Jiu-Tian [1 ,2 ]
Wang, Ru-Chuan [1 ,2 ,3 ]
Zhang, Yong-Can [1 ,2 ]
机构：
[1] College of Computer, Nanjing University of Posts and Telecommunications, Nanjing
[2] Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing
[3] Key Lab of Broadband Wireless Communication and Sensor Network Technology of Ministry of Education, Nanjing
来源：
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | 2014年 / 36卷 / 10期
关键词：
Compressive Sensing (CS); Data Fusion Tree (DFT); Sparse Random Projection (SRP); Wireless sensor networks;
D O I：
10.3724/SP.J.1146.2013.01621
中图分类号：
学科分类号：
摘要：
For the characteristic of energy-constrained in wireless sensor networks, considering routing strategy into the designing of the projection matrix, a Compressed Sensing algorithm based on Data Fusion Tree (CS-DFT) is proposed. It minimizes communication consumption by means of sparse random projection, and relevance between projection matrix and sparse basis is decreased in order to guarantee the data reconstruction quality while data fusion tree is generating. Simulation results show that, the proposed algorithm not only achieves a balance between reconstruction quality and energy consumption, but also has high adaptability to operate on a variety of data originated from different sparse basis.
引用
收藏
页码：2364 / 2369
页数：5
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