FBMC-based dispersion compensation using artificial neural network equalization for long reach-passive optical network

摘要

This paper presents a Filter Bank Multicarrier (FBMC), a viable waveform candidate for fifth generation (5G) communications using Staggered-Modulated Multitone (SMT). FBMC is preferred in optical communication because of its ability to work without Cyclic Prefix (CP). In any case, the operation of FBMC in optical access systems with Artificial Neural Networks (ANNs) has not been broadly explored either downstream or upstream. This work presents an advanced Nonlinear Feed-Forward Equalizer (NFFE) that makes use of multilayer ANN for dispersion compensation. ANN is trained to act as a filter with an extensive equalizer training which has the ability to mitigate dispersion and increase the performance of the system. The simulation work is used to study the performance of intensity modulated FBMC system with direct detection in Long Reach-Passive Optical Networks (LR-PONs).The transmission data rate is varied between 8 and 10 Gbps with the optical fiber length from 30 to 90 km of Standard Single Mode Fiber (SSMF). The obtained result suggests that FBMC system with ANN-NFFE equalizer fundamentally builds the resilience to the Chromatic Dispersion (CD) distortion, and a CP-less transmission is possible upto 90 km.