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Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping
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Published on: March 20, 2017

Channel coding and time-diversity for optical wireless links.

Fang Xu1, Ali Khalighi, Patrice Caussé

  • 1Ecole Centrale Marseille, Institut Fresnel, UMR CNRS 6133, Domaine Universitaire de Saint-Jérôme, 13397 Marseille cedex 20, France.

Optics Express
|January 23, 2009
PubMed
Summary
This summary is machine-generated.

Temporal diversity combats atmospheric turbulence in free space optical communication. Convolutional codes offer a good balance of performance and complexity for improving transmission link reliability.

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Area of Science:

  • Optical communication systems
  • Signal processing
  • Information theory

Background:

  • Atmospheric turbulence significantly degrades free space optical (FSO) communication performance.
  • Temporal diversity offers a viable strategy to mitigate these performance issues.
  • Channel coding and interleaving are key techniques for exploiting time diversity.

Purpose of the Study:

  • To investigate the effectiveness of various channel coding techniques for FSO links under different turbulence conditions.
  • To evaluate the impact of time diversity orders on system performance.
  • To assess receiver performance with channel estimation using training symbols.

Main Methods:

  • Simulation and analysis of different channel coding schemes (e.g., convolutional codes).
  • Evaluation across varying time diversity orders.
  • Testing under diverse atmospheric turbulence scenarios.
  • Incorporation of channel estimation techniques at the receiver.

Main Results:

  • Convolutional codes demonstrate a favorable trade-off between decoding complexity and performance enhancement.
  • The efficiency of channel coding is shown to be dependent on the time diversity order and turbulence intensity.
  • Channel estimation using training symbols impacts overall receiver performance.

Conclusions:

  • Exploiting temporal diversity through channel coding is an effective method for improving FSO communication reliability.
  • Convolutional codes are a practical choice for mitigating turbulence effects in FSO systems.
  • Channel estimation strategies are crucial for optimizing receiver performance in turbulent FSO channels.