Nonlinear Loss Compensation Method for Fiber Communication Based on Extended Nonlinear Operator

Tao Zhang; Xiaolong Tao; Boyi Liu; Liu Yang; Fengguang Luo; Yuebin Li; Yongming Hu; Yi Cai

doi:10.3788/AOS250858

Acta Optica Sinica, Volume. 45, Issue 16, 1606001(2025)

Nonlinear Loss Compensation Method for Fiber Communication Based on Extended Nonlinear Operator

Tao Zhang¹, Xiaolong Tao¹, Boyi Liu¹, Liu Yang^1、*, Fengguang Luo^2、**, Yuebin Li¹, Yongming Hu¹, and Yi Cai³

¹School of Microelectronics, Hubei Key Laboratory of Micro-Nanoelectronic Materials and Devices, Hubei University, Wuhan 430062, Hubei , China

²School of Optical and Electronic Information, National Engineering Research Center for Next Generation Internet Access-System, Huazhong University of Science and Technology, Wuhan 430074, Hubei , China

³School of Electronics and Information Engineering, Soochow University, Suzhou 215021, Jiangsu , China

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Figures & Tables(12)

Fig. 1. $k_{φ_{l o s s}}$ for every first 1024 symbols

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Fig. 2. Values of $k$ before and after sampling. (a) Before sampling; (b) after sampling

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Fig. 3. Coherent communication system structure

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Fig. 4. Principle of signal compensation and recovery in DSP stage

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Fig. 5. Q² of DC, DBP, adaptive DBP, and extended DBP (4-StPS-DBP) algorithms varying with launch power. (a) QPSK-1600 km; (b) 16QAM-1200 km; (c) 64QAM-400 km

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Fig. 6. Q² of DC, DBP, adaptive DBP, and extended DBP (1-StPS-DBP) algorithms varying with launch power. (a) QPSK-1600 km; (b) 16QAM-1200 km; (c) 64QAM-400 km

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Fig. 7. Q² for 16QAM at 17 and 19 spans. (a) 17 spans; (b) 19 spans

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Fig. 8. Q² of DBP, adaptive DBP, and extended DBP algorithms varying with number of compensation steps

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Fig. 9. Compensation performance and computational time varying with different particle numbers for extended DBP algorithm

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Fig. 10. Computational time of two algorthms under different particle numbers

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Table 1. Comparison of DC, DBP, adaptive DBP, and extended DBP
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Table 1. Comparison of DC, DBP, adaptive DBP, and extended DBP
Algorithm Linear operator Nonlinear operator
DC $\hat{D}$ —
DBP $\hat{D}$ $\hat{N} = i γ {|A|}^{2}$
Adaptive DBP $\hat{D}$ $\hat{N} = i γ n {|A|}^{2}, n \in [0,2]$
Extended DBP $\hat{D}$ $\hat{N} = i γ [{|A|}^{2} + \frac{1}{A} \frac{i}{ω_{0}} \frac{\partial ({|A|}^{2} A)}{\partial T}]$

Table 2. Computation complexity for different algorithms

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Table 2. Computation complexity for different algorithms

Algorithm	Addition complexity	Multiplication complexity
DBP	$N_{s t e p s} (2 N_{p o i n t s} l o g_{2} N_{p o i n t s})$	$N_{s t e p s} (N_{p o i n t s} l o g_{2} N_{p o i n t s} + 6) + 10$
Adaptive DBP	$N_{s t e p s} (2 N_{p o i n t s} l o g_{2} N_{p o i n t s})$	$N_{s t e p s} (N_{p o i n t s} l o g_{2} N_{p o i n t s} + 6) + 10$
Extended DBP	$N_{s t e p s} (2 + 2 N_{p o i n t s} l o g_{2} N_{p o i n t s})$	$N_{s t e p s} (N_{p o i n t s} l o g_{2} N_{p o i n t s} + 7) + 10$

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Tao Zhang, Xiaolong Tao, Boyi Liu, Liu Yang, Fengguang Luo, Yuebin Li, Yongming Hu, Yi Cai. Nonlinear Loss Compensation Method for Fiber Communication Based on Extended Nonlinear Operator[J]. Acta Optica Sinica, 2025, 45(16): 1606001

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