Blind identification of the number of sub-carriers for orthogonal frequency division multiplexing-based elastic optical networking
Blind identification of the number of sub-carriers for orthogonal frequency division multiplexing-based elastic optical networking
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DOI：
10.1016/j.optcom.2017.10.076
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发表时间：
2018-03
影响因子：
2.4
通讯作者：
Lei Zhao;Hengying Xu;Chenglin Bai
中科院分区：
文献类型：
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作者：
Lei Zhao;Hengying Xu;Chenglin Bai
在基于正交频分复用（OFDM）的弹性光网络（EON）中，快速、智能、鲁棒地识别OFDM弹性光网络信号中的未知参数势在必行。由于子载波的数量决定了子载波间距的大小，进而影响OFDM的符号周期和系统的抗色散能力，因此子载波数量的识别对系统其他关键参数的识别有着深远的影响。本文提出了一种基于ofdm的EON信号子载波的高阶循环累积量识别方法。特定的四阶循环累积量只存在于其子载波频率的位置。因此，可以通过检测周期频率来实现子载波数量的识别。本文提出的方案可分为估计频谱范围、计算高阶循环累积量和识别子载波数三个子阶段。当光信噪比（OSNR）在16dB ~ 22dB范围内变化时，实验成功识别了64 ~ 512个子载波数，从统计学角度看，平均识别绝对准确率（IAAs）超过94%。
In orthogonal frequency division multiplexing (OFDM)-based elastic optical networking (EON), it is imperative to identify unknown parameters of OFDM-based EON signals quickly, intelligently and robustly. Because the number of sub-carriers determines the size of the sub-carriers spacing and then affects the symbol period of the OFDM and the anti-dispersion capability of the system, the identification of the number of sub-carriers has a profound effect on the identification of other key parameters of the system. In this paper, we proposed a method of number identification for sub-carriers of OFDM-based EON signals with help of high-order cyclic cumulant. The specific fourth-order cyclic cumulant exists only at the location of its sub-carriers frequencies. So the identification of the number of sub-carriers can be implemented by detecting the cyclic-frequencies. The proposed scheme in our study can be divided into three sub-stages, i.e. estimating the spectral range, calculating the high-order cyclic cumulant and identifying the number of sub-carriers. When the optical signal-to-noise ratios (OSNR) varied from 16dB to 22dB, the number of sub-carriers (64–512) was successfully identified in the experiment, and from the statistical point of view, the average identification absolute accuracy (IAAs) exceeded 94%.