在基于低复杂度自动编码器和BiLSTM-ANN等级器的光纤无线集成系统中减轻非线性.
Optics express
|June 29, 2023
概括
我们开发了一种智能非线性补偿方法,用于光纤无线系统,使用堆叠自动编码器 (SAE) 和BiLSTM-ANN模型. 这种方法显著降低了比特错误率 (BER) 和高速数据传输的计算复杂性.
科学领域:
- 光学通信是指光学通信.
- 信号处理 信号处理
- 机器学习 机器学习
背景情况:
- 无线光纤综合系统面临非线性损害的挑战.
- 有效的补偿对于这些系统中的高速数据传输至关重要.
研究的目的:
- 为端到端 (E2E) 光纤无线系统提出和演示智能非线性补偿方法.
- 用先进的机器学习模型减轻非线性,减少计算复杂性.
主要方法:
- 使用堆叠自动编码器 (SAE) 进行非线性星座优化.
- 采用双向长期短期内存与ANN (BiLSTM-ANN) 非线性均衡器相结合.
- 综合主要组件分析 (PCA) 技术用于增强补偿.
主要成果:
- 在20公里SSMF和6米无线链路上成功传输了50 Gbps,32个QAM信号.
- 在比特错误率 (BER) 中降低了多达78%.
- 在3.8 × 10-3的BER时,显示了超过0.7dB的接收器灵敏度增益.
结论:
- 拟议的E2E非线性补偿方法有效地减轻了光纤无线系统的损害.
- 该系统在BER和接收器灵敏度上提供了显著的改进.
- 与经典模型相比,计算复杂性减少了10倍以上.
相关概念视频
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