  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.

Signal Processing;Artificial Intelligence