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Signal processing for enhancing railway communication by integrating deep learning and adaptive equalization techniques
by
Li, Jingjiao
, Yang, Cuilei
, Chang, Wei
, Wang, Yucai
in
Adaptive algorithms
/ Adaptive systems
/ Algorithms
/ Bandwidths
/ Bit error rate
/ Communication
/ Communications systems
/ Confidentiality
/ Data transmission
/ Deep Learning
/ Design
/ Direct current
/ Equalization
/ Error reduction
/ Fourier transforms
/ Health aspects
/ High speed
/ Light emitting diodes
/ Light reflection
/ Machine learning
/ Methods
/ Modulation
/ Navigation systems
/ Orthogonal Frequency Division Multiplexing
/ Railroads
/ Signal distortion
/ Signal processing
/ Signal Processing, Computer-Assisted
/ Signal quality
/ Signal reconstruction
/ Signal reflection
/ Signal-To-Noise Ratio
/ Simulation
/ Spectrum allocation
/ Spectrum analysis
/ Transmission efficiency
/ Wave division multiplexing
/ Wavelength
/ Wavelength division multiplexing
/ Wireless communications
/ Wireless Technology - instrumentation
2024
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Signal processing for enhancing railway communication by integrating deep learning and adaptive equalization techniques
by
Li, Jingjiao
, Yang, Cuilei
, Chang, Wei
, Wang, Yucai
in
Adaptive algorithms
/ Adaptive systems
/ Algorithms
/ Bandwidths
/ Bit error rate
/ Communication
/ Communications systems
/ Confidentiality
/ Data transmission
/ Deep Learning
/ Design
/ Direct current
/ Equalization
/ Error reduction
/ Fourier transforms
/ Health aspects
/ High speed
/ Light emitting diodes
/ Light reflection
/ Machine learning
/ Methods
/ Modulation
/ Navigation systems
/ Orthogonal Frequency Division Multiplexing
/ Railroads
/ Signal distortion
/ Signal processing
/ Signal Processing, Computer-Assisted
/ Signal quality
/ Signal reconstruction
/ Signal reflection
/ Signal-To-Noise Ratio
/ Simulation
/ Spectrum allocation
/ Spectrum analysis
/ Transmission efficiency
/ Wave division multiplexing
/ Wavelength
/ Wavelength division multiplexing
/ Wireless communications
/ Wireless Technology - instrumentation
2024
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Signal processing for enhancing railway communication by integrating deep learning and adaptive equalization techniques
by
Li, Jingjiao
, Yang, Cuilei
, Chang, Wei
, Wang, Yucai
in
Adaptive algorithms
/ Adaptive systems
/ Algorithms
/ Bandwidths
/ Bit error rate
/ Communication
/ Communications systems
/ Confidentiality
/ Data transmission
/ Deep Learning
/ Design
/ Direct current
/ Equalization
/ Error reduction
/ Fourier transforms
/ Health aspects
/ High speed
/ Light emitting diodes
/ Light reflection
/ Machine learning
/ Methods
/ Modulation
/ Navigation systems
/ Orthogonal Frequency Division Multiplexing
/ Railroads
/ Signal distortion
/ Signal processing
/ Signal Processing, Computer-Assisted
/ Signal quality
/ Signal reconstruction
/ Signal reflection
/ Signal-To-Noise Ratio
/ Simulation
/ Spectrum allocation
/ Spectrum analysis
/ Transmission efficiency
/ Wave division multiplexing
/ Wavelength
/ Wavelength division multiplexing
/ Wireless communications
/ Wireless Technology - instrumentation
2024
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Signal processing for enhancing railway communication by integrating deep learning and adaptive equalization techniques
Journal Article
Signal processing for enhancing railway communication by integrating deep learning and adaptive equalization techniques
2024
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Overview
With the increasing amount of data in railway communication system, the conventional wireless high-frequency communication technology cannot meet the requirements of modern communication and needs to be improved. In order to meet the requirements of high-speed signal processing, a high-speed communication signal processing method based on visible light is developed and studied. This method combines the adaptive equalization algorithm with deep learning and is applied to railway communication signal processing. In this research, the wavelength division multiplexing (WDM) and orthogonal frequency division multiplexing (OFDM) techniques are used, and fuzzy C equalization algorithm is used to softly divide the received signals, reduce signal distortion and interference suppression. The experimental results showed that increasing the step size could reduce the equalization effect, while increasing the modulation parameter will increase the bit error rate. Through deep learning to achieve channel equalization, visible light communication could effectively mitigate multi-path transmission and reflection interference, thereby reducing the bit error rate to the level of 0.0001. Under various signal-to-noise ratios, the system using the channel compensation method achieved the lowest bit error rate. This outcome was achieved by implementing hybrid modulation scheme, including Wavelength division multiplexing (WDM) and direct current-biased optical orthogonal frequency division multiplexing (DCO-OFDM) techniques. It has been proved that this method can effectively reduce the channel distortion when the receiver is moving. This study develops a dependable communication system, which enhances signal recovery, reduces interference, and improves the quality and transmission efficiency of railway communication. The system has practical application value in the field of railway communication signal processing.
Publisher
Public Library of Science
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