DeepChaos+: Signal Detection Quality Enhancement of High-Speed DP-16QAM Optical Fiber Communication Based on Chaos Masking Technique with Deep Generative Models

• DOI: 10.3390/photonics11100967
• Publication Date: 2024-10-17T08:42:15Z
• Authors: Dao Anh Vu; Nguyen Khoi Hoang Do; Huyen Ngoc Thi Ng...; Hieu Minh Dam; Thuy Thanh Thi Tran; Quyen Xuan Nguyen; Dung Cao Truong
• Keywords: SIGNAL (programming language)

In long-haul WDM (wavelength division multiplexing) optical communication systems utilizing the DP-16QAM modulation scheme, traditional methods for removing chaos have exhibited poor performance, resulting in a high bit error rate of 10−2 between original signal and removed signal. To address this issue, we propose DeepChaos+, machine learning-based approach removal transmission systems. Our framework comprises two key points: (1) DeepChaos+ automatically generates dataset that accurately reflects features signals system, which eliminates need time-consuming data simulation, streamlining process significantly; (2) it allows training lightweight model provides fast prediction times while maintaining accuracy. This both efficient reliable reconstruction. Through extensive experiments, demonstrate achieves accurate reconstruction with significantly reduced approximately 10−5. Additionally, exhibits efficiency terms processing time, facilitating results underscore effectiveness from By enhancing reliability chaotic secure channels fiber systems, holds potential to improve high-speed networks.