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2-D quantization scheme utilizing SOFM neural network clustering for a DRoF system

机译：利用SOFM神经网络聚类进行DROF系统的2-D量化方案

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摘要

A two-dimensional (2-D) quantization scheme for the digitized radio-over-fiber (DRoF) transmission system is proposed and experimentally demonstrated. By using a self-organizing feature map (SOFM) neural network clustering method to implement the 2-D quantization, the spectral efficiency of the DRoF system can be effectively improved, and a better transmission performance is achieved. Compared with the conventional scalar quantization based on pulse code modulation in the common public radio interface, the sampled sequence is constructed as a 2-D array, and the SOFM neural network clustering method is employed to obtain an optimized quantization codebook, which can achieve a better error vector magnitude performance with the same quantization bits. In the experiments, the proposed scheme for the DRoF transmission is demonstrated in a 25 km 5 Gbaud/lambda four-level pulse amplitude modulation (PAM-4) intensity modulation and direct detection optical link. For the 5G NR standard, carrier aggregations of 27, 20, 16, and 13 100 MHz orthogonal frequency division multiplexing with 4, 16, 64, and 256 QAM at quantization bits per sample of 3, 4, 5, and 6 are successfully achieved, respectively. (C) 2018 Optical Society of America
机译：一个两维（2-d）量化为数字化无线电过光纤（DRoF）传输系统的方案，提出和实验证明。通过使用自组织特征映射（SOFM）神经网络聚类方法来实现2-d量化时，DRoF系统的频谱效率可以被有效地提高，并且实现更好的传输性能。基于脉码调制在通用公共无线接口的常规标量量化相比，所采样的序列被构建为2-d阵列，并且采用SOFM神经网络聚类方法来获得一个优化的量化码本，从而可以实现一更好的误差矢量幅度性能与同量化比特。在实验中，对于DRoF传输所提出的方案是体现在一个25公里5波特/λ四电平脉冲幅度调制（PAM-4）强度调制和直接检测光链路。对于5G NR标准，27个载波聚合，20，16，和13 100 MHz的正交频分与4复用，16，64，并以每3样品，4个，5个量化比特256 QAM，和6被成功地实现， 分别。 （c）2018年光学学会

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  • 来源
    《Optics Letters》 |2018年第19期|共4页
  • 作者

    Ye Jia; Guo Yi; Li Peng; Yan Lianshan; Pan Wei; Zou Xihua;

  • 作者单位

    Southwest Jiaotong Univ Ctr Informat Photon &

    Commun Chengdu 611756 Sichuan Peoples R China;

    Southwest Jiaotong Univ Ctr Informat Photon &

    Commun Chengdu 611756 Sichuan Peoples R China;

    Southwest Jiaotong Univ Ctr Informat Photon &

    Commun Chengdu 611756 Sichuan Peoples R China;

    Southwest Jiaotong Univ Ctr Informat Photon &

    Commun Chengdu 611756 Sichuan Peoples R China;

    Southwest Jiaotong Univ Ctr Informat Photon &

    Commun Chengdu 611756 Sichuan Peoples R China;

    Southwest Jiaotong Univ Ctr Informat Photon &

    Commun Chengdu 611756 Sichuan Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 计量学;光学;
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