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This summary is machine-generated.

Fractional orbital angular momentum (FOAM) communication enhances channel capacity using phase dislocations and machine learning. This method achieves stable, accurate acoustic-vortex communication with improved resolution and information levels.

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Area of Science:

  • Acoustics
  • Optical Communications
  • Signal Processing

Background:

  • Fractional orbital angular momentum (FOAM) offers potential for infinite channel capacity in acoustic-vortex (AV) communications.
  • Current limitations include poor accuracy, stability, non-orthogonality, and interference in fractional AV beams.
  • Machine learning for acoustics is hindered by complex 2D measurement requirements, unlike in optics.

Purpose of the Study:

  • To develop a strategy for high-dimensional fractional AV communication using phase-dislocation-mediated methods.
  • To improve the accuracy, stability, and anti-interference capabilities of FOAM recognition.
  • To enable efficient information transmission in AV communication systems.

Main Methods:

  • Implementation of pair-FOAM multiplexing and circular sparse sampling.
  • Utilizing phase dislocation as a physical guide for FOAM recognition and sampling reduction.
  • Development of a convolutional neural network for stable and accurate communication, robust to turbulence and misalignment.

Main Results:

  • Experimental demonstration of 10-bit information transmission using 32-point dual-ring sampling within a specific topological charge scope.
  • Achieved a FOAM resolution of 0.2, significantly reducing divergence in AV communications.
  • Verified infinite channel capacity expansion through an improved FOAM resolution of 0.025.

Conclusions:

  • The proposed strategy significantly enhances OAM utilization, information level, and OAM resolution compared to previous works.
  • The technology offers advantages in high dimension, high speed, and low divergence for AV communication.
  • This approach holds promise for next-generation acoustic-vortex communication systems.