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Adaptive Fuzzy Logic Deep-Learning Equalizer for Mitigating Linear and Nonlinear Distortions in Underwater Visible

Radhakrishnan Rajalakshmi1, Sivakumar Pothiraj2, Miroslav Mahdal3

  • 1Department of Electronics and Communication Engineering, Ramco Institute of Technology, Rajapalayam 626117, India.

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This study introduces an adaptive fuzzy logic deep-learning equalizer for underwater visible light communication (UVLC). The novel equalizer significantly reduces errors and complexity, enabling high-speed, reliable underwater data transmission.

Keywords:
adaptive fuzzy logicdeep learningdeep-learning equalizerequalizationsparrow search optimizationunderwater visible light communication

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Area of Science:

  • Optical Communications
  • Signal Processing
  • Machine Learning

Background:

  • Underwater visible light communication (UVLC) offers a green alternative for aquatic environments but faces challenges like signal attenuation and turbulence.
  • Existing UVLC systems struggle with linear and nonlinear impairments, limiting performance.

Purpose of the Study:

  • To develop an advanced equalizer for 64 Quadrature Amplitude Modulation-Component minimal Amplitude Phase shift (QAM-CAP) modulated UVLC systems.
  • To mitigate linear and nonlinear impairments in UVLC, enhancing data transmission reliability and speed.

Main Methods:

  • An adaptive fuzzy logic deep-learning equalizer (AFL-DLE) utilizing complex-valued neural networks and constellation partitioning.
  • The Enhanced Chaotic Sparrow Search Optimization Algorithm (ECSSOA) was employed to optimize the equalizer's performance.

Main Results:

  • Achieved a 55% reduction in bit error rate and a 45% reduction in distortion rate.
  • Demonstrated a 48% decrease in computational complexity and a 75% reduction in computation cost.
  • Maintained a high transmission rate of 99%.

Conclusions:

  • The proposed AFL-DLE effectively addresses impairments in UVLC systems.
  • This approach facilitates high-speed, online data processing for advanced underwater communication systems.