Abstract In this paper, a back propagation neural network-based function approximation scheme is proposed to provide the capacity of the nonuniform quantization (FABP) in intensity modulated direct detection-based optical filter… Click to show full abstract
Abstract In this paper, a back propagation neural network-based function approximation scheme is proposed to provide the capacity of the nonuniform quantization (FABP) in intensity modulated direct detection-based optical filter bank multicarrier (IMDD-FBMC) system. In the means of leveraging this scheme, the quantization noise can be reduced to further improve the ratio of Signal-to-Quantization noise, namely SQNR. Further, with the help of the nonlinear programming, the optimal quantization levels are accurately calculated. And, to validate the feasibility of our method, the simulation and experiment investigation are conducted on the 10-Gb/s transmission system with optical order offset quadrature amplitude modulation based optical orthogonal frequency division multiplexing (OQAM-OFDM) signals through 80-km fiber. Results verified that, our scheme can achieve the error vector magnitude (EVM) improvement of ∼ 2.0% and received sensitivity improvement of at least 2 dB in the same quantization bit case compared with uniform quantization scheme.
               
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