부산대학교 도서관

A chaotic optical communication scheme assisted by artificial intelligence (AI) method is proposed. Different from other traditional solutions, the chaos synchronization of the proposed scheme is accomplished via an AI-based optoelectronic oscillator (AI-OEO) model and a QPSK driving signal distorted by chromatic dispersion. Specifically, the distorted driving signal excites the chaotic AI-OEO model to generate the chaotic signal for encryption and decryption. One significant advantage is that the strict dependence of chaos synchronization on physical devices can be reduced by using deep learning technology to model the actual experimental chaotic system. The proposed scheme has been experimentally validated in a chaotic-encrypted 256 Gbit/s (32-GBaud) polarization-multiplexed 16QAM system over 1600 km standard single-mode fiber (SSMF). The results show that the BER performance after 1600 km transmission is lower than the 20% FEC threshold limit (BER = 2.4 × 10 −2 ). Furthermore, we conducted a comprehensive security assessment of the system, comparing it with traditional chaotic encryption schemes and performing a detailed analysis of the key space and key sensitivity. The proposed scheme is compatible with the existing high-speed coherent optical fiber communication systems, and the realization of precise chaos synchronization only requires ensuring that the driving signal is decoded without errors at the receiver. We believe that it has the potential to become a candidate solution for bidirectional high-speed secure communication with low complexity and cost.