• Acta Optica Sinica
  • Vol. 42, Issue 9, 0906001 (2022)
Xiongwei Yang1, Feng Zhao2、*, Linxian Zhao1, and Zhao Meng2
Author Affiliations
  • 1School of Communication and Information Engineering, Xi′an University of Post and Telecommunications, Xi′an 710121, Shaanxi, China
  • 2School of Electronic Engineering, Xi′an University of Posts and Telecommunications, Xi′an 710121, Shaanxi, China
  • show less
    DOI: 10.3788/AOS202242.0906001 Cite this Article Set citation alerts
    Xiongwei Yang, Feng Zhao, Linxian Zhao, Zhao Meng. Phase Recovery Algorithm for Adaptive Probabilistic Shaping Signal Based on K-means[J]. Acta Optica Sinica, 2022, 42(9): 0906001 Copy Citation Text show less
    Flow chart of K-means clustering algorithm
    Fig. 1. Flow chart of K-means clustering algorithm
    Schematic diagram of phase recovery algorithm
    Fig. 2. Schematic diagram of phase recovery algorithm
    Schematic diagram of system simulation
    Fig. 3. Schematic diagram of system simulation
    Variation of normalized conversion factor with modulus variance
    Fig. 4. Variation of normalized conversion factor with modulus variance
    Radius relocation results. (a) Information entropy is 3.78 bit·symbol-1; (b) information entropy is 3.56 bit·symbol-1; (c) information entropy is 3.30 bit·symbol-1
    Fig. 5. Radius relocation results. (a) Information entropy is 3.78 bit·symbol-1; (b) information entropy is 3.56 bit·symbol-1; (c) information entropy is 3.30 bit·symbol-1
    BER and EVM after signal recovery under different OSNR. (a) BER; (b) EVM
    Fig. 6. BER and EVM after signal recovery under different OSNR. (a) BER; (b) EVM
    NGMI curves of 16QAM with different information entropy and different line width
    Fig. 7. NGMI curves of 16QAM with different information entropy and different line width
    BER and EVM after signal recovery under different OSNR. (a) BER; (b) EVM
    Fig. 8. BER and EVM after signal recovery under different OSNR. (a) BER; (b) EVM
    NGMI curves of 64QAM with different information entropy for different line width
    Fig. 9. NGMI curves of 64QAM with different information entropy for different line width
    Simulation results. (a)(b) 4 bit·symbol-1 16QAM; (c)(d) 2.8 bit·symbol-1 16QAM; (e)(f) 6 bit·symbol-1 64QAM; (g)(h) 4.71 bit·symbol-1 64QAM
    Fig. 10. Simulation results. (a)(b) 4 bit·symbol-1 16QAM; (c)(d) 2.8 bit·symbol-1 16QAM; (e)(f) 6 bit·symbol-1 64QAM; (g)(h) 4.71 bit·symbol-1 64QAM
    Xiongwei Yang, Feng Zhao, Linxian Zhao, Zhao Meng. Phase Recovery Algorithm for Adaptive Probabilistic Shaping Signal Based on K-means[J]. Acta Optica Sinica, 2022, 42(9): 0906001
    Download Citation