MZM Nonlinear Equalization by Sinusoidal Subcarrier Modulation Combined with LM-BP Neural Network
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Abstract:
In order to reduce the nonlinear effect of Mach-Zehnder modulator (MZM) on optical transmission signals in intensity modulation and direct detection (IM-DD) systems, a joint scheme of sinusoidal subcarrier modulation (SSM) and Levenberg-Marquardt back propagation (LM-BP) neural network is proposed in this paper. The scheme uses sine wave as the subcarrier to carry the PAM4 signals to equalize the distorted signals after MZM modulation, and then the LM-BP algorithm removes the remaining inter-symbol interference (ISI). This scheme uses sine wave modulation to solve the problem of additional ISI caused by triangular wave modulation. And the joint scheme reduces the complexity of the algorithm than using only the 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 50Gbit/s PAM4 signals for 80km without relaying under the premise of dispersion compensation, and the BER can reach 10-5.
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Project Supported:
The National Key Technologies R&D Program of China
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