| Optical performance monitoring (OPM) is a promising technology to improve control of transmission- and physical-layer fault management,which is essential for the operation of complex and transparent wavelength-division-multiplexing (WDM) transmission and switching systems. Within various OPM techniques, monitoring of the optical signal-to-noise ratio (OSNR) is very important as OSNR is one of the most fundamental parameters indicating the signal transmission performance. Since traditional out-band OSNR monitoring is not accurate in a dynamic WDM network with optical add-drop modules (OADM) due to the intermediate filtering, a number of techniques have been reported to monitor the in-band OSNR, among them, OSNR monitor based on interferometry is very promising because that it exploits the coherence difference between signal and amplified spontaneous emission (ASE) to calculate the OSNR, making it intrinsically independent to chromatic dispersion (CD), polarization mode dispersion (PMD) and polarized noise.Therefore, this dissertation mainly focuses on the technologies of optical performance monitoring, especially the optical signal-to-noise ratio monitoring technologies based on interferometry. The main research efforts are summarized as follow.1. A novel in-band OSNR monitor is proposed and experimentally demonstrated for WDM signal. By using a Lyot-Sagnac interferometer,the monitor realized OSNR measurement from 7.5?25 dB (within an accuracy of ±0.5 dB) for 4-channel 40 Gbaud NRZ-QPSK signals,without requirement for prior knowledge of the noise-free coherence properties of signal. Further investigation proved that this OSNR monitor had high tolerance to chromatic dispersion (0?1152 ps/nm),first-order polarization mode dispersion (0?100 ps), and polarized noise. Moreover,the monitor worked very well even with input optical power as low as-8.24 dBm, and within wavelength in C-band.2. In order to resolve the complexity and deviations in date-processing due to manual operations in interferometry-based OSNR monitoring, an intelligent data acquisition and processing system is designed and realized for OSNR monitoring, which is based on data acquisition card. In order to process data in real time, we exploited multi-thread processes, including data acquisition thread, data storage thread and data calculation thread. Moreover, three smoothing algorithms are introduced in data calculation thread to reduce the noise/jitter in collected data. Besides, test experiments were carried out to verify the feasibility of the intelligent data processing system, with injection of electrical periodic signals with different amplitude and different noise level. We found that the noise was reduced significantly with all three smoothing algorithms, and can reduced more with multi-time smoothing processes. Among the three smoothing algorithms, seven-point-one-time smoothing algorithm is the best. Considering the application in OSNR monitoring and time cost in data process, data smoothing twice with seven-point-one-time smoothing algorithm is the optimal processing algorithm.3?The above intelligent data processing system was implemented experimentally in an MZI-based OSNR monitoring system. Experimental results show that smoothing algorithms significantly reduced the noise in acquisition data and monitoring errors, in turn enlarged OSNR monitoring range from 7?25.6dB to 6.5?30.6dB, which is very impressive. Compared with results from multi-time smoothing processes,we find that all three smoothing algorithms are effective in post-processing OSNR monitoring results, among them, data smoothing twice with seven-point-one-time smoothing algorithm is optimal. At last,we investigated and confirmed the robustness of our intelligent data processing system with changing the system parameters, such as input optical powers and repetition frequency of the bias voltage to phase modulator. |
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