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Compressive Sensing Based Data Collection in Wireless Sensor Networks

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DOI: 10.23977/iotea.2016.11005 | Downloads: 63 | Views: 6587


Fu Jie 1, Liu Yuhong 1


1 School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou, 730070, China

Corresponding Author

Liu Yuhong


In order to improve the energy efficiency by reducing the amount of the data delivered in Wireless Sensor Networks(WSNs), a Compressive Sensing(CS) based data collection scheme considering the correlation in temporal-spatial domain is studied in this paper. Kronecker product is applied to construct the sparse basis in the joint domain. The simulation results show that due to the huge amount of sensor nodes, by exploiting the dependency in spatial domain, the data number can be reduced distinctly. The high recovery accurancy can still be achieved.


Wireless Sensor Networks, Compressive Sensing, Spatial-Temporal correlation, Kronecker Product, Data Collection, Energy Efficiency


Yuhong, L. and Jie, F. (2016) Compressive Sensing Based Data Collection in Wireless Sensor Networks. Internet of Things (IoT) and Engineering Applications (2016) 1: 23-28.


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