论文标题
Wiener相位噪声通道的几何星座与低复杂性降解器形状
Geometric Constellation Shaping with Low-complexity Demappers for Wiener Phase-noise Channels
论文作者
论文摘要
我们表明，在优化的，基于机器学习的光学通信系统的基于机器学习的Demapper中，将相位和正交组件与几何星座分开降低了所需的计算复杂性，同时保持其良好的性能。
We show that separating the in-phase and quadrature component in optimized, machine-learning based demappers of optical communications systems with geometric constellation shaping reduces the required computational complexity whilst retaining their good performance.
