研究目的
Investigating the possibility of improving the stability of radio frequency transfer in DWDM fiber optic networks by compensating temperature-induced differential delay fluctuations caused by dispersion compensation fibers.
研究成果
The proposed method significantly improves long-term stability of frequency transfer in DWDM networks by compensating DCF-induced differential delay fluctuations using temperature data. Stability improved by 5-10 times for long averaging times, with reductions in frequency offset. The method is effective across different routes and can be adapted for real-time correction, though further improvements in sensor accuracy and model refinement are possible.
研究不足
The method relies on accurate temperature sensors and DCF length data, which may have inaccuracies; it does not account for thermal behavior of other optical modules or non-identical temperature distributions along fiber paths; dynamic modeling is simplified and may not capture all thermal inertia effects; post-processing requires synchronization between data sources.
1：Experimental Design and Method Selection:
The study involved setting up frequency transfer systems over three long-haul DWDM routes (1550 km, 1380 km, 1000 km) using alien wavelength service. The method included modeling the impact of DCF temperature variations on differential delay using equations (1) and (2), with dynamic modeling via transfer functions in Matlab System Identification Toolbox.
2：Sample Selection and Data Sources:
Three routes in the PIONIER network with soil-deployed fibers; temperature data from DCF sensors collected via SNMP; phase fluctuations measured with a phase comparator.
3：List of Experimental Equipment and Materials:
ELSTAB terminals, passive hydrogen maser, VCH-314 phase comparator, FSP3000 series devices by ADVA Optical Networking, DCF modules with temperature sensors.
4：Experimental Procedures and Operational Workflow:
Frequency signals (10 MHz) transmitted via DWDM; temperature and phase data recorded with 1-second resolution for 3-5 days; data post-processed to apply corrections based on DCF temperature models.
5：Data Analysis Methods:
Used Modified Allan Deviation (MDEV) for stability analysis; RMS error calculations; system identification in Matlab for dynamic modeling.
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