非线性WDM光纤链路上的端到端光语义通信
End-to-End Optical Semantic Communication over a Nonlinear WDM Fiber Link
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中文总结 AI 辅助
针对非线性WDM光纤链路，提出端到端光语义通信系统，直接映射图像为信道符号，实现联合分类与重建，在MNIST上以更少符号保持高准确率并扩展传输距离。
中文摘要 AI 辅助
新兴的光网络应用越来越多地将接收数据用于推理和控制，而非精确的源再现，这为以比特级保真度换取更远的传输距离和更高的效率创造了机会。我们提出了一种端到端的光语义通信系统，用于在非线性波分复用（WDM）光纤信道上进行联合图像分类和重建。该系统将每幅图像直接映射为固定长度的信道符号序列，该序列保留与任务相关的信息，无需显式的源压缩或信道编码。在MNIST数据集上的实验覆盖了从-9到+3 dBm的发射功率、长达800 km的光纤长度以及16、64和256正交幅度调制（QAM）格式。在0 dBm下，所有测试的链路长度和调制阶数下，分类准确率保持在98.92%至99.31%之间，同时在每个测试的调制阶数下，所需的传输符号数少于低密度奇偶校验（LDPC）编码的JPEG基线。这些结果表明，语义通信通过仅传递与任务相关的信息，可以同时扩展光传输距离并减少传输资源。
英文摘要
Emerging optical-network applications increasingly use received data for inference and control rather than exact source reproduction, creating an opportunity to trade bit-level fidelity for greater transmission reach and efficiency. We propose an end-to-end optical semantic communication system for joint image classification and reconstruction over a nonlinear wavelength-division multiplexed (WDM) fiber channel. The system maps each image directly into a fixed-length sequence of channel symbols that preserves task-relevant information, without explicit source compression or channel coding. Experiments on the MNIST dataset cover launch powers from -9 to +3 dBm, fiber lengths up to 800 km, and 16-, 64-, and 256-Quadrature Amplitude Modulation (QAM) formats. At 0 dBm, classification accuracy remains between 98.92% and 99.31% across all tested link lengths and modulation orders, while requiring fewer transmitted symbols than a Low-Density Parity-Check (LDPC)-coded JPEG baseline at every tested modulation order. These results show that semantic communication can simultaneously extend optical reach and reduce transmission resources by conveying only task-relevant information.
发表机构
- Politecnico di Torino（都灵理工大学）
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