研究目的
To demonstrate the feasibility of a novel space division multiplexing technique based on the classification of speckle patterns measured at the output of a standard multimode optical fiber, aiming to increase the capacity of telecommunication links.
研究成果
The study successfully demonstrates a novel space division multiplexing scheme using speckle pattern classification in standard multimode fibers. The technique is robust to mode-mixing and polarization scrambling effects, offering a potential increase in telecommunication link capacity. Future work could explore the use of few-mode fibers to mitigate intermodal dispersion and further optimize the classification methods for higher channel counts.
研究不足
The number of channels an MMF can support is limited by the minimal required spatial separation of optical inputs on the fiber’s entrance facet and the potency of the receiver’s speckle classification method. The technique's performance is also affected by intermodal dispersion in long-haul data transmission.
1：Experimental Design and Method Selection:
The study employs a novel space division multiplexing technique using speckle pattern classification. It involves injecting multiple optical signals into a standard multimode optical fiber and analyzing the resulting speckle patterns at the fiber's output.
2：Sample Selection and Data Sources:
The experiments use standard gradient index multimode fibers with lengths varying from 3 to 46 meters. The optical signals are generated by laser diodes operating around 639 nm.
3：List of Experimental Equipment and Materials:
The setup includes Thorlabs HL6358MG laser diodes, lenses for beam collimation and focusing, neutral density filters, beamsplitters, and a high-resolution Spiricon 12-bit CCD camera (model SP620U) for imaging speckle patterns.
4：Experimental Procedures and Operational Workflow:
The procedure involves controlling the position, wavelength, and polarization of the optical inputs to the fiber, recording the resulting speckle patterns, and analyzing these patterns to detect the state of the input signals.
5：Data Analysis Methods:
The analysis includes calculating cross-correlations between speckle patterns and using linear classifiers to efficiently extract the transmitted data from the speckle patterns.
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