利用迁移学习有效识别调制格式

D. Jha, Jitendra K. Mishra
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引用次数: 0

摘要

利用迁移学习(TL)技术,提出了一种有效的光信噪比(OSNRs)在20 ~ 30 dB范围内的调制格式识别(MFI)。创建传输设置以演示8QAM、16QAM、64QAM和128QAM系统的技术。由于TL的自学习能力,它可以用图像处理的方法来处理星座图。研究结果表明,即使在低信噪比条件下,所提出的技术也可以准确地检测出调制格式,分类率高达100%。所提出的方法可以智能地分析基本硬件以实现MFI,分析结果可用于识别不同传输速率下的附加调制方案,从而更好地管理光学系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient Modulation Format Identification Using Transfer Learning
An efficient modulation format identification (MFI) at an optical signal-to-noises ratios (OSNRs) spanning from 20 to 30 dB is proposed using the transfer learning (TL) technique. Transmission setup are created to demonstrate the technique for 8QAM, 16QAM, 64QAM, and 128QAM systems. TL can process constellation diagrams from an image processing approach owing to its self-learning capabilities. The obtained research shows that even at low OSNR, the suggested techniques may accurately be utilized to detect the modulation format with classification rates up to 100%The suggested method can intelligently analyse the basic hardware to allow MFI, and the analysis results are used to identify additional modulation schemes at various transmission rates for better management of optical systems.
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