A novel method using half-symbol delay tap sampling technique for monitoring timing misalignment between data modulator and pulse carver in 33% duty-cycle return-to-zero on-off keying (RZ-OOK), 50% duty-cycle RZ-OOK, and carrier-suppressed RZ-OOK optical transmitters is proposed and experimentally demonstrated. The presented scheme is able to not only identify three RZ-OOK signals but also determine both the timing misalignment magnitude and direction. The effectiveness of the proposed scheme is validated by simulation and experiment in 10-Gbps optical systems, and its robustness against imperfections of the transmitter is also analyzed.
A technique using artificial neural networks trained with parameters derived from reconstructed eye diagrams for
optical performance monitoring in 40-Gbps optical duobinary (ODB) system is demonstrated. Firstly, the optical signal
is asynchronously sampled by short pulse in the nonlinear medium such as semiconductor optical amplifier and highly
nonlinear fiber, the sampled and collected data is then processed by improved software synchronization algorithm to
obtain reconstructed eye diagrams without data clock recovery. Secondly, the features of the reconstructed eye diagrams
are extracted to train the three-layer preceptor artificial neural network. Finally, the outputs of trained neural network are
used to monitor multiple optical signal impairments. Simulation experiments of optical signal noise ratio (OSNR),
chromatic dispersion (CD) and polarization mode dispersion (PMD) monitoring in 40-Gbps ODB system is presented.
The proposed monitoring scheme can accurately identify simultaneous impairment with the root-mean-square (RMS)
monitoring error less than 3%.
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