2023 Vol.6 Oct.N05

• Title: Deep learning-based wireless channel estimation for IoT of agricultural irrigation equipment
• Name: Wei Dou
• Company: School of Finance and Economics, Qinghai University,Xining,810016,China
• Abstract:

  The current conventional wireless channel estimation algorithm mainly achieves channel estimation by comparing the lead symbol energy with the threshold value at the receiver side, which leads to poor estimation accuracy due to the lack of gain analysis for low signal-to-noise ratio conditions. In this regard, a deep learning-based IoT wireless channel estimation method for agricultural irrigation equipment is proposed. Combined with the variation characteristics of wireless channels, the channel gain variation due to multipath fading is analyzed. And combined with the deep learning algorithm, the channel estimation is modeled as an image super-resolution reconstruction problem, and the channel is estimated using the deconvolution operation. In the experiments, the designed channel estimation algorithm is tested for the estimation accuracy. The final results can prove that the algorithm has a low root mean square error value when the proposed method is used for channel estimation and has a more desirable channel estimation performance.

  
  

• Keyword: deep learning; channel estimation; irrigation equipment; Internet of Things; deconvolution operations;
• DOI: 10.12250/jpciams2023090704
• Citation form: Wei Dou.Deep learning-based wireless channel estimation for IoT of agricultural irrigation equipment [J]. Computer Informatization and Mechanical System,2023,Vol.6,pp.12-17

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