IEEE Photonics Journal (Jan 2022)

Modified Mean-Power-Distribution-Based Nonlinear Coefficient Optimization for Digital Back-Propagation in High-Baud-Rate Optical Systems

  • Meng Yang,
  • Pinjing He,
  • Aiying Yang,
  • Peng Guo

DOI
https://doi.org/10.1109/JPHOT.2022.3217341
Journal volume & issue
Vol. 14, no. 6
pp. 1 – 8

Abstract

Read online

The digital back-propagation (DBP) is an effective algorithm to compensate for the nonlinear impairments in high-baud-rate and long-haul optical systems. The nonlinear coefficient of the DBP algorithm is optimized based on the mean power at the step position. However, when the number of steps per span of the DBP algorithm is fixed below the optimum step number to constrain computational complexity, the optimum nonlinear coefficient is sensitive to the number of steps per span. In this paper, we used the average value of the mean power over the step size to optimize the nonlinear coefficient of the DBP algorithm. The modified mean-power-distribution-based nonlinear coefficient optimization scheme was applied to constant step-size DBP (MMPD-CS-DBP) and logarithmic step-size DBP (MMPD-LS-DBP) algorithms in 30 × 80 km SSMF single-channel Nyquist 64 GBaud and 5 × 64 GBaud Nyquist WDM polarization multiplexing 16QAM systems, respectively. Simulation results showed that the optimum nonlinear coefficient of the MMPD-CS-DBP and MMPD-LS-DBP algorithms was the nonlinear coefficient of the optical fiber and was robust to the number of steps per span.

Keywords