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Interdimensional Interference Equalizing Using Recurrent Neural Network for Multi-Dimensional Optical Transmission
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DOI：10.1109/ACCESS.2024.3350194.png)
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Abstract
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During multi-dimensional optical transmission, because of photodetector (PD) operation as a square law detector, signals get distorted when they are modulated on polarization and phase due to interdimensional interference (IDI) by intensity-modulated signals. We propose an IDI mitigation technique using recurrent neural network for multi-dimensional optical transmission. The signal transmission performance of the proposed equalization technique was experimentally analyzed. The performance of the proposed system was verified using the symbol error rate (SER).
Keywords:
Multi-dimensional optical modulation
interdimensional interference (IDI)
recurrent neural network (RNN)
optical access network
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3.6
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29.4W
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