Compressed Sensing Based Low Power Data Transmission Systems in Mobile Sensor Networks 


Vol. 41,  No. 11, pp. 1589-1597, Nov.  2016


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  Abstract

In this paper, we propose a system in a large-scale environment, such as desert and ocean, that can reduce the overall transmission power consumption in mobile sensor network. It is known that the transmission power consumption in wireless sensor network is proportional to the square of transmission distance. Therefore, if the locations of mobile sensors are far from the sink node, the power consumption required for data transmission increases, leading to shortened operating time of the sensors. Hence, in this paper, we propose a system that can reduce the power consumption by allowing to transmit data only if the transmission range of the sensors is within a predetermined distance. Moreover, the energy efficiency of the overall sensor network can even be improved by reducing the number of data transmissions at the sink node to gateway based on compressed sensing. The proposed system is actually implemented using Arduino and Raspberry Pi and it is confirmed that source data can be approximately decoded even when the gateway received encoded data fewer than the required number of data from the sink node. The performance of the proposed system is analyzed in theory.

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  Cite this article

[IEEE Style]

J. Hong, J. Kwon, M. Kwon, H. Park, "Compressed Sensing Based Low Power Data Transmission Systems in Mobile Sensor Networks," The Journal of Korean Institute of Communications and Information Sciences, vol. 41, no. 11, pp. 1589-1597, 2016. DOI: .

[ACM Style]

Jiyeon Hong, Jungmin Kwon, Minhae Kwon, and Hyunggon Park. 2016. Compressed Sensing Based Low Power Data Transmission Systems in Mobile Sensor Networks. The Journal of Korean Institute of Communications and Information Sciences, 41, 11, (2016), 1589-1597. DOI: .

[KICS Style]

Jiyeon Hong, Jungmin Kwon, Minhae Kwon, Hyunggon Park, "Compressed Sensing Based Low Power Data Transmission Systems in Mobile Sensor Networks," The Journal of Korean Institute of Communications and Information Sciences, vol. 41, no. 11, pp. 1589-1597, 11. 2016.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880