High-speed optical communication systems may suffer from a combination of impairments such as memory effect and nonlinear behavior of the optoelectronic components. Nonlinear digital pre-distortion (DPD) is one of the well-known technique to alleviate these effects. As typical implementation of Volterra-based DPD is considered complex and consumes high power, more efficient orthogonal-based Volterra series representation has been proposed. Previous works offered ways to perform efficient grading of the most dominant dimensions based on the combination of the dimensions variances and the signal projection. Here, it is shown that normalization of the data dynamic range further improves this method and decreases significantly the number of required dimensions. Using normalization combined with the previous methods, maximizes the DPD performance by means of error vector magnitude (EVM) and bit error rate (BER), while minimizing the DPD complexity in the terms of required series dimensions. Extensive simulation and lab measurements indicate a potential saving of up to 87% in the number of dimensions with a negligible performance penalty.

中文翻译：

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尺寸减小的正交 Volterra DPD 的分级优化

高速光通信系统可能会受到诸如记忆效应和光电组件非线性行为等多种损害的影响。非线性数字预失真 (DPD) 是缓解这些影响的众所周知的技术之一。由于基于 Volterra 的 DPD 的典型实现被认为是复杂的并且消耗高功率，因此已经提出了更有效的基于正交的 Volterra 级数表示。以前的工作提供了基于维度方差和信号投影的组合对最主要维度进行有效分级的方法。在这里，表明数据动态范围的归一化进一步改进了这种方法并显着减少了所需的维数。使用归一化结合前面的方法，通过误差矢量幅度 (EVM) 和误码率 (BER) 最大限度地提高 DPD 性能，同时最大限度地降低所需串联维度方面的 DPD 复杂性。广泛的模拟和实验室测量表明，维度数量最多可节省 87%，而性能损失可忽略不计。