2017
DOI: 10.1016/j.yofte.2016.12.006
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Laser linewidth and fiber nonlinearity tolerance study of C-16QAM compared to square 16QAM in coherent OFDM system

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Cited by 4 publications
(3 citation statements)
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“…HS-12QAM is obtained by combining GS-12QAM with PS and the Euclidean distance between HS-12QAM constellation points is n times GS, where n is the scaling factor under the power normalization constraint. Studies prove that a circle constellation significantly improves the phase noise and fiber nonlinear effects tolerance compared with a square constellation 8 , 25 , 26 . Therefore, GS-8/12QAM and HS-8/12QAM are more advantageous than R-8/12QAM and PS-8/12QAM in optical fiber communication systems.…”
Section: Principles Of Hybrid Geometric-probabilistic Shapingmentioning
confidence: 98%
See 1 more Smart Citation
“…HS-12QAM is obtained by combining GS-12QAM with PS and the Euclidean distance between HS-12QAM constellation points is n times GS, where n is the scaling factor under the power normalization constraint. Studies prove that a circle constellation significantly improves the phase noise and fiber nonlinear effects tolerance compared with a square constellation 8 , 25 , 26 . Therefore, GS-8/12QAM and HS-8/12QAM are more advantageous than R-8/12QAM and PS-8/12QAM in optical fiber communication systems.…”
Section: Principles Of Hybrid Geometric-probabilistic Shapingmentioning
confidence: 98%
“…Studies prove that a circle constellation significantly improves the phase noise and fiber nonlinear effects tolerance compared with a square constellation. 8,25,26 Therefore, GS-8/ 12QAM and HS-8/12QAM are more advantageous than R-8/12QAM and PS-8/12QAM in optical fiber communication systems. The analysis of noise-resistance ability is presented in Sec.…”
Section: Minimum Euclidean Distance and Constellation Figure Of Merit...mentioning
confidence: 99%
“…The CMA algorithm has robust convergence which can be used to make the eye open at the beginning of equalization. After opening the eye, the DD-LMS algorithm can be used to decrease the residual error [4] .…”
Section: Joint Equalization Algorithmmentioning
confidence: 99%