Compressed sensing in wireless sensor networks under complex conditions of Internet of things
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Based on the analysis of the traditional compressed sensing method, the problem of multi signal processing in the Internet of things is discussed in detail. A class of distributed compressive sensing methods based on time correlation is proposed. By means of time correlation, a linear regression method is used to segment the experimental signals. On this basis, the joint sparse model of distributed compressed sensing is improved, and a compression matrix is designed to extract the linear fitting part of the signal. Then, the adaptive compressed sensing is used to compress the signal processed by the compressed matrix, thus forming a complete new scheme of compressed sensing signal processing.
KeywordsInternet of things Wireless sensor networks Compressed sensing
This work was supported by the Fundamental Research Fund for The Central Universities (2015QNA39) and the National Natural Science Funds of China (51674245).
- 2.Rathore, P., Rao, A.S., Rajasegarar, S., Vanz, E., Gubbi, J., Palaniswami, M.: Real-time urban microclimate analysis using internet of things. IEEE Internet Things J. 99, 1 (2017)Google Scholar
- 5.Vieira, R.G., Cunha, A.M.D., Camargo, A.P.D.: An energy management method of sensor nodes for environmental monitoring in amazonian basin. Wireless Netw. 20(3), 1–15 (2015)Google Scholar
- 7.Chen, S., Liu, J., Wang, K., Wu, M.: A hierarchical adaptive spatio-temporal data compression scheme for wireless sensor networks. Wireless Netw. 10, 1–10 (2017)Google Scholar