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Quasi-light Storage for Optical Data Packets
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用Kramers-Kronig接收器对64-QAM信号进行非线性等效的光子储计算
Sarah Masaad1, Emmanuel Gooskens1, Stijn Sackesyn1
1Photo-nics Research Group, INTEC Department, Ghent University - imec, Ghent 9052, Belgium.
Nanophotonics (Berlin, Germany)
|December 5, 2024
概括
光子储库是一种机器学习系统,有效减少光纤通信中的信号误差. 这项技术为数据中心间网络提供了低功耗,低延迟的解决方案.
科学领域:
- 光学通信是指光学通信的应用.
- 机器学习 机器学习
- 信号处理 信号处理
背景情况:
- 光子储为光学处理提供了能源效率和速度.
- 在光纤通信系统中数字信号均等化面临着非线性性带来的挑战.
- 非线性诱导的错误来自光纤自相调节和调节器响应.
研究的目的:
- 模拟一个被动光子储库,以针对非线性诱导的错误.
- 用克拉默斯-克罗尼格接收器评估光子容器的性能.
- 评估系统在数据中心间通信中的适用性.
主要方法:
- 模拟了一个被动光子储库.
- 采用了64级的正方形振幅调制信号.
- 使用克莱默斯-克罗尼格 (KK) 接收器进行直接检测.
- 通过反向传播通过接收管道训练的读出重量.
主要成果:
- 在高达100公里的光纤长度上,实现的比特错误率低于1×10−3.
- 超过了线性光学前均衡器基准.
- 证明有效的非线性缓解.
结论:
- 被动光子储存器与KK接收器相结合,为光纤通信的非线性提供了一个有希望的解决方案.
- 该系统的硬件简单性,低功耗和低延迟适用于数据中心之间的应用程序.
- 这种方法可以为未来的通信网络推进光学信号处理.
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