Evolving fuzzy neural network equalization of channel impulse response in optical mode division multiplexing
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Abstract
Optical mode division multiplexing (MDM) systems suffer from the inter-symbol interference (ISI) issues due to nonlinear channel impairments in multimode fiber from mode coupling and modal dispersion. Existing equalization algorithms in MDM systems such as least mean square (LMS) and recursive least squares (RLS) operate linearly and thus far, are unable to effectively mitigate the nonlinear channel impairments. To address this issue, a nonlinear evolving fuzzy neural network (EFuNN) equalization scheme was developed in MATLAB to reshape the channel impulse response of a MDM system comprising five Laguerre-Gaussian (LG) modes at the transmitter to five reference Gaussian pulses at separate time intervals at the receiver in order to mitigate the effects of ISI from nonlinear channel impairments.
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