Peak Power Distribution based Nonlinear Parameter Optimization for Digital Back-propagation

Abstract

A nonlinear parameter optimized scheme based on peak power distribution is proposed for DBP algorithm. The 1 dB Q-factor gain is achieved in the simulation transmission of 32-GBaud PDM 16-QAM signal with a 24*100km single channel.

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

“…The LS-DBP can reduce the optimum step number (the minimum step number per span to achieve the maximum Q-factor) of the CS-DBP algorithm [18]. Another way is to improve the nonlinear coefficient optimization scheme [19]- [22]. D. Rafique et al optimized the nonlinear coefficient based on the correlation of signal power in neighboring symbols [19].…”

“…M. Secondini et al proposed an enhanced DBP algorithm that combined the benefits of split-step and perturbation-based approaches to reduce computational complexity [20] and more recently, a smoothing learned DBP using a neural network was proposed to reduce the computational complexity of DBP algorithm [21]. In our previous work, a nonlinear coefficient optimization scheme based on the peak power distribution of Gaussian pulse was proposed to improve the NLC performance of the CS-DBP algorithm for a 2400 km SSMF 32 GBaud polarization-multiplexing (PM) 16 quadrature amplitude modulation (16QAM) optical transmission system [22].…”