MZM nonlinear equalization by sinusoidal subcarrier modulation combined with LM-BP neural network

In order to mitigate the nonlinear effects of Mach-Zehnder modulator(MZM)on optical transmission signals in intensity modulation and direct detection(IM-DD)systems,a combined approach utilizing sinusoidal subcarrier modulation(SSM)and the Levenberg-Marquardt back propagation(LM-BP)neural network is proposed in this paper.The method employs a sine wave as the subcarrier to carry the 4 pulse amplitude modulation(PAM4)signals,aiming to equalize the distorted signals after MZM modulation.Subsequently,the LM-BP algorithm eliminates any remaining inter-symbol interference(ISI).This scheme uses sine wave modulation to solve the problem of additional ISI caused by triangular wave modulation.Furthermore,this combined approach simplifies the algorithm complexity compared to solely relying on a neural network equalizer.In this paper,the performance of SSM-LM-BP scheme is simulated and analyzed in IM-DD system.The results show that the joint scheme outperforms the triangular wave modulation scheme as well as the neural network algorithm after transmitting 50 Gbit/s PAM4 signals for 80 km without relays under the conditions of dispersion compensation,and the symbol error rate(SER)can be as low as 10-5.