352 research outputs found

    Compact silicon multimode waveguide spectrometer with enhanced bandwidth

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    Compact, broadband, and high-resolution spectrometers are appealing for sensing applications, but difficult to fabricate. Here we show using calibration data a spectrometer based on a multimode waveguide with 2 GHz resolution, 250 GHz bandwidth, and a 1.6 mm × 2.1 mm footprint. Typically, such spectrometers have a bandwidth limited by the number of modes supported by the waveguide. In this case, an on-chip mode-exciting element is used to repeatably excite distinct collections of waveguide modes. This increases the number of independent spectral channels from the number of modes to this number squared, resulting in an extension of the usable range

    Optical Frequency Comb Noise Characterization Using Machine Learning

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    A novel tool, based on Bayesian filtering framework and expectation maximization algorithm, is numerically and experimentally demonstrated for accurate frequency comb noise characterization. The tool is statistically optimum in a mean-square-error-sense, works at wide range of SNRs and offers more accurate noise estimation compared to conventional methods

    An ultra-fast method for gain and noise prediction of Raman amplifiers

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    A machine learning method for prediction of Raman gain and noise spectra is presented: it guarantees high-accuracy (RMSE < 0.4 dB) and low computational complexity making it suitable for real-time implementation in future optical networks controllers

    Widely Linear Equalization for IQ Imbalance and Skew Compensation in Optical Coherent Receivers

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    Deep Learning of Geometric Constellation Shaping including Fiber Nonlinearities

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    A new geometric shaping method is proposed, leveraging unsupervised machine learning to optimize the constellation design. The learned constellation mitigates nonlinear effects with gains up to 0.13 bit/4D when trained with a simplified fiber channel model.Comment: 3 pages, 6 figures, submitted to ECOC 201

    Phase Noise Compensation for Nonlinearity-Tolerant Digital Subcarrier Systems With High-Order QAM

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    The fundamental penalty of subcarrier modulation (SCM) with independent subcarrier phase noise processing is estimated. It is shown that the fundamental signal-to-noise ratio (SNR) penalty related to poorer phase noise tolerance of decreased baudrate subcarriers increases significantly with modulation format size and can potentially exceed the gains of the nonlinear tolerance of SCM. A low-complexity algorithm is proposed for joint subcarrier phase noise processing, which is scalable in the number of subcarriers and recovers almost entirely the fundamental SNR penalty with respect to single-carrier systems operating at the same net data-rate. The proposed algorithm enables high-order modulation formats with high count of subcarriers to be safely employed for nonlinearity mitigation in optical communication systems
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