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Zhai S, Qian Z, Yang B, Wang X. Data Reconstructing Algorithm in Unreliable Links Based on Matrix Completion for Heterogeneous Wireless Sensor Networks. INT J PATTERN RECOGN 2019. [DOI: 10.1142/s0218001419510121] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
In heterogeneous wireless sensor networks, the data collection method based on compressed sensing technology is susceptible to packet loss and noise, which leads to a decrease in data reconstruction accuracy in unreliable links. Combining compressed sensing and matrix completion, we propose a clustering optimization algorithm based on structured noise matrix completion, in which the cluster head transmits the compressed sampling data and compression strategy to the base station. The algorithm we proposed can reduce the energy consumption of the node in the process of data collection, redundant data and transmission delay. The rank-1 matrix completion algorithm constructs an extremely sparse observation matrix, which is adopted by the sink node to complete the reconstruction of the whole network data. Simulation experiments show that the proposed algorithm reduces network transmission data, balances node energy consumption, improves data transmission efficiency and reconstruction accuracy, and extends the network life cycle.
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Affiliation(s)
- Shuang Zhai
- College of Communication Engineering, Jilin University, Changchun 130012, P. R. China
- Institute of Computer Science and Engineering, Changchun University of Technology, Changchun 130012, P. R. China
| | - Zhihong Qian
- College of Communication Engineering, Jilin University, Changchun 130012, P. R. China
| | - Bingtao Yang
- College of Communication Engineering, Jilin University, Changchun 130012, P. R. China
| | - Xue Wang
- College of Communication Engineering, Jilin University, Changchun 130012, P. R. China
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