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Related Concept Videos

Turbulent Flow01:24

Turbulent Flow

185
Turbulent flow is characterized by unpredictable fluctuations in velocity and pressure, which result in a chaotic fluid movement distinct from the orderly patterns of laminar flow. While laminar flow is governed by smooth, parallel layers with minimal mixing, turbulent flow exhibits highly irregular, three-dimensional patterns. This behavior arises due to instabilities in the fluid's velocity profile, and amplifies as the flow velocity increases. Minor disturbances, known as turbulent...
185
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  11. Turbulence-resistant Free Space Optical Communication Via Chaotic Block-matching And 3d Filtering.
  1. Home
  3. Research Domains
  5. Engineering
  7. Communications Engineering
  9. Signal Processing
  11. Turbulence-resistant Free Space Optical Communication Via Chaotic Block-matching And 3d Filtering.

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Turbulence-resistant free space optical communication via chaotic block-matching and 3D filtering.

Tingwei Wu, Hanxiang Mou, Yutong He

    Optics Express
    |April 4, 2024

    View abstract on PubMed

    Summary
    This summary is machine-generated.

    A new Chaotic Block-Matching and 3D (C-BM3D) filter enhances free space optical (FSO) communication security and reduces noise in turbulent channels. This algorithm shows superior performance in peak signal-to-noise ratio and image similarity, improving bit error rate.

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    Area of Science:

    • Optical Communications
    • Signal Processing
    • Information Security

    Background:

    • Free space optical (FSO) communication is susceptible to atmospheric turbulence, degrading signal quality and security.
    • Existing filtering algorithms struggle to effectively mitigate turbulence-induced noise and enhance data security simultaneously.

    Purpose of the Study:

    • To introduce a novel Chaotic Block-Matching and Three-Dimensional (C-BM3D) filtering algorithm.
    • To evaluate the performance of C-BM3D in mitigating noise and enhancing security in FSO communication under turbulent conditions.

    Main Methods:

    • The proposed C-BM3D algorithm was developed for noise reduction and security enhancement.
    • Experimental comparisons were conducted against Chaotic Non-Local Means (C-NLM), Chaotic Gaussian, and Chaotic Median filtering.
  • Performance was assessed using Log-normal and Gamma-Gamma turbulence models, evaluating Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Signal-to-Noise Ratio (SNR), and Bit Error Rate (BER).

    • Main Results:

    • C-BM3D achieved high PSNR values (up to 96.2956 and 93.2853) in weak turbulence under Log-normal and Gamma-Gamma models, respectively.
    • Superior image similarity (SSIM near 1) was observed with C-BM3D in Log-normal turbulent channels.
    • C-BM3D demonstrated the highest SNR and an improved BER of at least 15 dB compared to other methods.

    Conclusions:

    • The C-BM3D filtering algorithm effectively removes noise and enhances security in FSO communication systems operating in turbulent channels.
    • C-BM3D shows significant advantages in turbulence resistance and data security, making it a promising solution for next-generation FSO communication.