论文标题
语义光纤通信系统
Semantic optical fiber communication system
论文作者
论文摘要
当前的光通信系统最小化位或符号错误,而无需考虑数字位背后的语义含义,从而传输了许多不必要的信息。我们提出并实验证明了语义光纤通信(SOFC)系统。使用深度学习从源中提取语义信息,而不是将信息编码为传输的位。然后,生成的语义符号通过光纤直接传输。与基于位的结构相比,SOFC系统实现了更高的信息压缩和更稳定的性能,尤其是在低接收的光功率状态下,并增强了针对光学链路障碍的鲁棒性。这项工作在人类的分析思维水平上引入了智能的光学通信系统,这是迈向当前光学通信体系结构突破的重要一步。
The current optical communication systems minimize bit or symbol errors without considering the semantic meaning behind digital bits, thus transmitting a lot of unnecessary information. We propose and experimentally demonstrate a semantic optical fiber communication (SOFC) system. Instead of encoding information into bits for transmission, semantic information is extracted from the source using deep learning. The generated semantic symbols are then directly transmitted through an optical fiber. Compared with the bit-based structure, the SOFC system achieved higher information compression and a more stable performance, especially in the low received optical power regime, and enhanced the robustness against optical link impairments. This work introduces an intelligent optical communication system at the human analytical thinking level, which is a significant step toward a breakthrough in the current optical communication architecture.