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  • Optica Publishing Group  (5)
  • Guo, Dong  (5)
  • 2020-2024  (5)
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  • Optica Publishing Group  (5)
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Language
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  • 2020-2024  (5)
Year
  • 1
    Online Resource
    Online Resource
    Probabilistic neural network equalizer for nonlinear mitigation in OAM mode division multiplexed optical fiber communication
    Optica Publishing Group ; 2022
    In:  Optics Express Vol. 30, No. 26 ( 2022-12-19), p. 47957-
    Details
    In: Optics Express, Optica Publishing Group, Vol. 30, No. 26 ( 2022-12-19), p. 47957-
    Abstract: Orbital angular momentum (OAM) mode-division multiplexing (MDM) is a key technique to achieve ultra-high-capacity optical fiber communications. However, the high nonlinear impairment from optoelectronic devices, such as spatial light modulators, modulators, and photodiodes, is a long-standing challenge for OAM-MDM. In this paper, an equalizer based on a probabilistic neural network (PNN) is presented to mitigate the nonlinear impairment for an OAM-MDM fiber communication system with 32 GBaud Nyquist pulse amplitude modulation-8 (PAM8) intensity-modulation direct-detection (IM-DD) signals. PNN equalizer can calculate the distribution of the nonlinearity using Bayesian decision theory and thus mitigate the stochastic nonlinear impairment of the received signal. Experimental results show that compared with the convolutional neural network (CNN) equalizer, the PNN equalizer improves the receiver sensitivity by 0.6dB and 2dB for two OAM modes with l  = + 3 and l  = + 4 at the 20% FEC limit, respectively. Moreover, compared with Volterra or CNN equalizers, the PNN equalizer can reduce the computation complexity significantly, which has great potential to mitigate the nonlinear signal distortions in high-speed IM-DD OAM-MDM fiber communication systems.
    Type of Medium: Online Resource
    ISSN: 1094-4087
    URL: Article
    DOI: 10.1364/OE.456908
    Language: English
    Publisher: Optica Publishing Group
    Publication Date: 2022
    detail.hit.zdb_id: 1491859-6
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  • 2
    Online Resource
    Online Resource
    400 Gbit/s 4 mode transmission for IM/DD OAM mode division multiplexing optical fiber communication with a few-shot learning-based AffinityNet nonlinear equalizer
    Optica Publishing Group ; 2023
    In:  Optics Express Vol. 31, No. 14 ( 2023-07-03), p. 22622-
    Details
    In: Optics Express, Optica Publishing Group, Vol. 31, No. 14 ( 2023-07-03), p. 22622-
    Abstract: Nonlinear impairment in a high-speed orbital angular momentum (OAM) mode-division multiplexing (MDM) optical fiber communication system presents high complexity and strong stochasticity due to the massive optoelectronic devices. In this paper, we propose an Affinity Network (AffinityNet) nonlinear equalizer for an OAM-MDM intensity-modulation direct-detection (IM/DD) transmission with four OAM modes. The labeled training and testing signals from the OAM-MDM system can be regarded as “small sample” and “large target”, respectively. AffinityNet can be used to build an accurate nonlinear model using “small sample” based on few-shot learning and can predict the stochastic characteristic nonlinearity of OAM-MDM with a high level of generalization. As a result, the AffinityNet nonlinear equalizer can effectively compensate the stochastic nonlinearity in the OAM-MDM system, despite the large difference between the training and testing signals due to the stochastic nonlinear impairment. An experiment was conducted on a 400 Gbit/s transmission with four OAM modes using a pulse amplitude modulation-8 (PAM-8) signal over a 2 km ring-core fiber (RCF). Our experimental results show that the proposed nonlinear equalizer outperformed the conventional Volterra equalizer with improvements in receiver sensitivity of 1.7, 1.8, 3, and 3.3 dB for the four OAM modes at the 15% forward error correction (FEC) threshold, respectively. In addition, the proposed equalizer outperformed a convolutional neural network (CNN) equalizer with improvements in receiver sensitivity of 0.8, 0.5, 0.9, and 1.4 dB for the four OAM modes at the 15% FEC threshold. In the experiment, a complexity reduction of 37% and 83% of the AffinityNet equalizer is taken compared to the conventional Volterra equalizer and CNN equalizer, respectively. The proposed equalizer is a promising candidate for a high-speed OAM-MDM optical fiber communication system.
    Type of Medium: Online Resource
    ISSN: 1094-4087
    URL: Article
    DOI: 10.1364/OE.492795
    Language: English
    Publisher: Optica Publishing Group
    Publication Date: 2023
    detail.hit.zdb_id: 1491859-6
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  • 3
    Online Resource
    Online Resource
    Probabilistic shaping and forward error correction scheme employing uneven segmentation mapping for data center optical communication
    Optica Publishing Group ; 2021
    In:  Optics Express Vol. 29, No. 4 ( 2021-02-15), p. 6209-
    Details
    In: Optics Express, Optica Publishing Group, Vol. 29, No. 4 ( 2021-02-15), p. 6209-
    Abstract: The combination of probabilistic shaping (PS) technology and forward error correction (FEC) technology can significantly boost the performance of a transmission system. In this paper, we propose a probabilistic shaping distribution matching algorithm employing uneven segmentation for data center optical networks, while keeping extremely low computational complexity for both encoding and decoding. Based on the proposed probabilistic shaping distribution matching algorithm, we develop a novel integrated scheme of PS and FEC coding that lifts the restrictions on the use of FEC technology and increases the use of interleaver. An experiment used to evaluate the probabilistically shaped data transmission is successfully conducted over a 25 km standard single-mode fiber (SSMF) with 16 quadrature amplitude modulation (16-QAM). Simultaneously, we use a simulation software to analyze the bit error rate performance at higher resolution. The results show that the joint coding scheme can achieve a 0.4dB performance improvement compared with the single FEC system.
    Type of Medium: Online Resource
    ISSN: 1094-4087
    URL: Article
    DOI: 10.1364/OE.416175
    Language: English
    Publisher: Optica Publishing Group
    Publication Date: 2021
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  • 4
    Online Resource
    Online Resource
    Hidden conditional random field-based equalizer for the 3D-CAP-64 transmission of OAM mode-division multiplexed ring-core fiber communication
    Optica Publishing Group ; 2023
    In:  Optics Express Vol. 31, No. 18 ( 2023-08-28), p. 28747-
    Details
    In: Optics Express, Optica Publishing Group, Vol. 31, No. 18 ( 2023-08-28), p. 28747-
    Abstract: As a key technique for achieving ultra-high capacity optical fiber communications, orbital angular momentum (OAM) mode-division multiplexing (MDM) is affected by severe nonlinear impairments, including modulation related nonlinearities, square-law nonlinearity and mode-coupling-induced nonlinearity. In this paper, an equalizer based on a hidden conditional random field (HCRF) is proposed for the nonlinear mitigation of OAM-MDM optical fiber communication systems with 20 GBaud three-dimensional carrierless amplitude and phase modulation-64 (3D-CAP-64) signals. The HCRF equalizer extracts the stochastic nonlinear feature of the OAM-MDM 3D-CAP-64 signals by estimating the conditional probabilities of the hidden variables, thereby enabling the signals to be classified into subclasses of constellation points. The nonlinear impairment can then be mitigated based on the statistical probability distribution of the hidden variables of the OAM-MDM transmission channel in the HCRF equalizer. Our experimental results show that compared with a convolutional neural network (CNN)-based equalizer, the proposed HCRF equalizer improves the receiver sensitivity by 2 dB and 1 dB for the two OAM modes used here, with l  =  + 2 and l  =  + 3, respectively, at the 7% forward error correction (FEC) threshold. When compared with a Volterra nonlinear equalizer (VNE) and CNN-based equalizer, the computational complexity of the proposed HCRF equalizer was found to be reduced by 30% and 41%, respectively. The bit error ratio (BER) performance and reduction in computational complexity indicate that the proposed HCRF equalizer has great potential to mitigate nonlinear distortions in high-speed OAM-MDM fiber communication systems.
    Type of Medium: Online Resource
    ISSN: 1094-4087
    URL: Article
    DOI: 10.1364/OE.495146
    Language: English
    Publisher: Optica Publishing Group
    Publication Date: 2023
    detail.hit.zdb_id: 1491859-6
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  • 5
    Online Resource
    Online Resource
    Carrier phase recovery friendly probabilistic shaping scheme based on a quasi-Maxwell–Boltzmann distribution model
    Optica Publishing Group ; 2020
    In:  Optics Letters Vol. 45, No. 17 ( 2020-09-01), p. 4883-
    Details
    In: Optics Letters, Optica Publishing Group, Vol. 45, No. 17 ( 2020-09-01), p. 4883-
    Abstract: A novel probabilistic shaping (PS) scheme based on the quasi-Maxwell–Boltzmann (quasi-MB) distribution model is proposed in order to solve the incompatibility between PS and carrier phase recovery (CPR) algorithms, such as blind phase search (BPS) and principal component-based phase estimation (PCPE). In the proposed quasi-MB model, the same occurrence probability is assigned to each constellation point on the same square-ring, rather than on the same circle. Signals obeying the quasi-MB model have superior CPR friendliness compared to traditional PS signals. For a PS 64 quadrature amplitude modulation system, the simulation results indicate up to 51% and 21% normalized generalized mutual information (NGMI) improvements for PCPE and BPS, respectively. Experimental verification of the proposed quasi-MB scheme was demonstrated in a 10 Gbaud coherent detection system. The results show that when the optical signal-to-noise ratio (OSNR) is low, the quasi-MB model can help the BPS algorithm to achieve better NGMI performance and, when the OSNR is high, the proposed model can also solve the incompatibility between the PCPE algorithm and PS.
    Type of Medium: Online Resource
    ISSN: 0146-9592 , 1539-4794
    URL: Article
    DOI: 10.1364/OL.402198
    Language: English
    Publisher: Optica Publishing Group
    Publication Date: 2020
    detail.hit.zdb_id: 243290-0
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