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An improved algorithm of segmented orthogonal matching pursuit based on wireless sensor networks

Author

Listed:
  • Xinmiao Lu
  • Yanwen Su
  • Qiong Wu
  • Yuhan Wei
  • Jiaxu Wang

Abstract

Aiming at the problems of low data reconstruction accuracy in wireless sensor networks and users unable to receive accurate original signals, improvements are made on the basis of the stagewise orthogonal matching pursuit algorithm, combined with sparseness adaptation and the pre-selection strategy, which proposes a sparsity adaptive pre-selected stagewise orthogonal matching pursuit algorithm. In the framework of the stagewise orthogonal matching pursuit algorithm, the algorithm in this article uses a combination of a fixed-value strategy and a threshold strategy to screen the candidate atom sets in two rounds to improve the accuracy of atom selection, and then according to the sparsity adaptive principle, the sparse approximation and accurate signal reconstruction are realized by the variable step size method. The simulation results show that the algorithm proposed in this article is compared with the orthogonal matching pursuit algorithm, regularized orthogonal matching pursuit algorithm, and stagewise orthogonal matching pursuit algorithm. When the sparsity is 35 

Suggested Citation

  • Xinmiao Lu & Yanwen Su & Qiong Wu & Yuhan Wei & Jiaxu Wang, 2022. "An improved algorithm of segmented orthogonal matching pursuit based on wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 18(3), pages 15501329221, March.
    • Handle: RePEc:sae:intdis:v:18:y:2022:i:3:p:15501329221077165
    DOI: 10.1177/15501329221077165
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