Self-adaptive probabilistically shaped star-carrier-less amplitude/phase passive optical network based on simulated annealing algorithm

Shun Han; Bo Liu; Yaya Mao; Xing Xu; Xiangyu Wu; Jianxin Ren; Lei Jiang; Jianye Zhao; Lijia Zhang

doi:10.1117/1.OE.58.2.026101

5 February 2019 Self-adaptive probabilistically shaped star-carrier-less amplitude/phase passive optical network based on simulated annealing algorithm

Shun Han, Bo Liu, Yaya Mao, Xing Xu, Xiangyu Wu, Jianxin Ren, Lei Jiang, Jianye Zhao, Lijia Zhang

Author Affiliations +

Optical Engineering, Vol. 58, Issue 2, 026101 (February 2019). https://doi.org/10.1117/1.OE.58.2.026101

Abstract

A self-adaptive probabilistically shaped (PS) star-carrier-less amplitude/phase (CAP)-24 modulated passive optical network (PON) is proposed to adaptively adjust the probability distribution of the signal points. The proposed scheme is capable of accommodating different channels and transmission distances to obtain the optimal probability distribution. The employment of the simulated annealing algorithm in the constellation can significantly reduce the average signal power, as well as facilitating the flexible deployment and enhancement of the PON system. The experimental results show that the self-adaptive optimal signal transmission can be acquired when the probability ratio of signal points located in the three well-designed rings of the CAP-24 constellation is set as 0.724:0.175:0.101. Compared with the general PS-star-CAP-32 signal, the self-adaptive PS-star-CAP-24 signal has a gain of 1.5 dB at the 7% hard decision forward error correction (HD-FEC) limit. What is more, the proposed PS self-adaptive PS-star-CAP-24 can outperform the general PS-star-CAP-24 constellation by 0.2 dB at the 7% HD-FEC limit.

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Shun Han, Bo Liu, Yaya Mao, Xing Xu, Xiangyu Wu, Jianxin Ren, Lei Jiang, Jianye Zhao, and Lijia Zhang "Self-adaptive probabilistically shaped star-carrier-less amplitude/phase passive optical network based on simulated annealing algorithm," Optical Engineering 58(2), 026101 (5 February 2019). https://doi.org/10.1117/1.OE.58.2.026101

Received: 17 December 2018; Accepted: 14 January 2019; Published: 5 February 2019

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