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Probabilistic shaping and neural network-based optimization for a nonlinear frequency division multiplexing system

机译:基于概率整形和神经网络的非线性频分复用系统优化

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摘要

A joint scheme introducing probabilistic shaping (PS) at the transmitter and utilizing a neural network (NN) equalizer at the receiver is proposed to improve the performance of the b-modulated nonlinear frequency division multiplexing (NFDM) system. Through a numerical simulation, we demonstrate that PS plays a leading role for low launch power case, which improves the performance of the system effectively, while the NN equalizer's superiority appears in a high launch power region, whose main role is to weaken the correlation among subcarriers for improving system performance. The proposed scheme would enlighten the optimum modulation and detection schemes of the NFDM system. (C) 2021 Optical Society of America
机译:该文提出一种在发射机处引入概率整形(PS)并在接收机处利用神经网络(NN)均衡器的联合方案,以提高b调制非线性频分复用(NFDM)系统的性能。通过数值仿真,结果表明,PS在低发射功率情况下起着主导作用,有效地提高了系统的性能,而NN均衡器的优势出现在高发射功率区域,其主要作用是削弱子载波之间的相关性,从而提高系统性能。该方案为NFDM系统的最佳调制和检测方案提供了启示。(C) 2021 年美国光学学会

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