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Learning diffractive optical communication around arbitrary opaque occlusions.

Md Sadman Sakib Rahman1,2,3, Tianyi Gan1,3, Emir Arda Deger1

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This study introduces a novel free-space optical communication method that bypasses opaque blockages. Using a trained neural network and diffractive decoder, it transmits optical data around obstacles at light speed.

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Area of Science:

  • Optics and Photonics
  • Communication Systems
  • Artificial Intelligence

Background:

  • Free-space optical communication (FSOC) is hindered by occlusions blocking the light path.
  • Maintaining communication links in the presence of arbitrary, opaque obstacles is a significant challenge.

Purpose of the Study:

  • To demonstrate a direct communication scheme that can circumvent fully opaque, arbitrarily shaped occlusions in free-space optical links.
  • To develop a robust method for transmitting optical information around line-of-sight blockages.

Main Methods:

  • A deep learning approach was used to jointly train an electronic neural network encoder and a passive, all-optical diffractive network decoder.
  • The system was designed to transfer optical information around occlusions of arbitrary shapes.
  • Experimental validation was performed in the terahertz spectrum using a 3D-printed diffractive decoder.

Main Results:

  • The trained encoder-decoder pair successfully transmitted arbitrary optical information around opaque occlusions.
  • Information decoding occurred at the speed of light via passive light-matter interactions.
  • The system demonstrated resilience to unknown changes in occlusion shape and size.

Conclusions:

  • This novel scheme enables free-space optical communication around opaque obstacles, overcoming a major limitation.
  • The demonstrated method is scalable to various wavelengths and offers high data-rate potential for future communication systems.
  • The use of a jointly trained neural network and diffractive decoder provides a robust and efficient solution for non-line-of-sight optical communication.