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RETRACTED: Signal processing for enhancing railway communication by integrating deep learning and adaptive

Yucai Wang1, Wei Chang1, Jingjiao Li1

  • 1Department of Rail Transit, Shijiazhuang Institute of Railway Technology, Shijiazhuang, China.

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A new visible light communication method enhances railway data processing by combining adaptive equalization and deep learning. This approach significantly reduces signal distortion and interference, improving communication quality and efficiency.

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Area of Science:

  • Optical Communications
  • Signal Processing
  • Railway Engineering

Background:

  • Conventional wireless high-frequency communication in railways is insufficient for growing data demands.
  • Need for improved high-speed signal processing in railway communication systems.
  • Visible light communication (VLC) offers a potential solution for enhanced data transmission.

Purpose of the Study:

  • To develop and study a high-speed communication signal processing method based on visible light for railway applications.
  • To combine adaptive equalization algorithms with deep learning for improved signal processing.
  • To enhance the quality and transmission efficiency of railway communication systems.

Main Methods:

  • Implemented a visible light communication system integrating adaptive equalization and deep learning.
  • Utilized wavelength division multiplexing (WDM) and orthogonal frequency division multiplexing (OFDM) techniques.
  • Employed fuzzy C equalization algorithm for signal division and interference suppression, alongside deep learning for channel equalization.

Main Results:

  • Deep learning-based channel equalization effectively mitigated multi-path and reflection interference in VLC.
  • Achieved a significantly reduced bit error rate (BER) of 0.0001.
  • A hybrid modulation scheme (WDM and DCO-OFDM) demonstrated the lowest BER across various signal-to-noise ratios, effectively reducing channel distortion even with receiver movement.

Conclusions:

  • The developed visible light communication method provides a dependable solution for railway communication signal processing.
  • The system enhances signal recovery, reduces interference, and improves overall communication quality and transmission efficiency.
  • This approach holds practical application value for modernizing railway communication infrastructure.