Successive Eigenvalue Removal for Multi-Soliton Spectral Amplitude Estimation
Successive Eigenvalue Removal for Multi-Soliton Spectral Amplitude Estimation
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DOI：
10.1109/jlt.2020.2994156
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发表时间：
2020-04
影响因子：
4.7
通讯作者：
Alexander Span;Vahid Aref;H. Buelow;S. Brink
中科院分区：
文献类型：
--
作者：
Alexander Span;Vahid Aref;H. Buelow;S. Brink
基于光学非线性傅立叶变换的通信系统需要对信号的非线性频谱进行精确估计，通常通过对信号样本的分段逼近方法计算。为了改进多孤子脉冲的频谱估计，提出了一种连续特征值去除算法。它利用了达布变换的一个性质，允许从非线性谱中去除特征值。这导致更小的脉冲持续时间和更小的带宽。在去除信号的特征值后，依次估计频谱系数。作为一个有益的应用，我们表明该算法通过迭代地减少脉冲持续时间来降低计算复杂度。
Optical nonlinear Fourier transform-based communication systems require an accurate estimation of a signal's nonlinear spectrum, computed usually by piecewise approximation methods on the signal samples. We propose an algorithm, named successive eigenvalue removal, to improve the spectrum estimation of a multi-soliton pulse. It exploits a property of the Darboux transform that allows removing eigenvalues from the nonlinear spectrum. This results in a smaller pulse duration and smaller bandwidth. The spectral coefficients are estimated successively after removing the eigenvalues of a signal. As a beneficial application, we show that the algorithm decreases the computational complexity by iteratively reducing the pulse duration.