Innovative system demonstrates enhanced transmission quality in WDM fiber-optic systems, suggesting efficient control via AI.
Nonlinear optical effects, including self-phase modulation (SPM), cross-phase modulation (XPM), and four-wave mixing (FWM), significantly limit the performance of modern wavelength-division multiplexing (WDM) fiber-optic systems, leading to signal quality degradation, increased bit error rate (BER), and reduced maximum transmission distance. To overcome these limitations, this paper proposes an innovative hybrid intelligent adaptive fiber-optic system (IAF) that combines electro-optic and acousto-optic control of the refractive index in liquid crystal photonic crystal fibers (LC-PCF). The use of transparent indium-tin-oxide (ITO) electrodes and piezoelectric transducers enables precise and rapid dynamic modulation of the nonlinear coefficientn2 and effective mode area Aeff. This allows real-time adaptation of the optical properties of the medium, minimizing nonlinear distortions and enhancing transmission quality. A key element of the system is the integration of advanced artificial intelligence methods, specifically deep neural networks (DNN) and reinforcement learning (RL) algorithms, which optimize control parameters based on continuous signal monitoring. Such intelligent control accounts for variable operating conditions, accurately detecting and compensating nonlinear effects. Particular attention is given to metrological aspects: comprehensive sensor calibration methods and error assessment techniques have been developed to ensure measurement reliability and stability. This increases system robustness and its ability to maintain optimal parameters over extended periods. Numerical simulation results demonstrate significant system performance improvements: a reduction in the nonlinear coefficient γby 25...50%, a decrease in BER by 20...35%, and an increase in maximum transmission distance by 15...25% in high-speed 400G and 800G WDM systems. The proposed hybrid intelligent adaptive system shows great potential for deployment in backbone, submarine, and long-haul fiber-optic networks, enhancing efficiency, reliability, and adaptability of modern telecommunication infrastructures.
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Коханов et al. (2025) studied this question.
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