Channel monitoring for optical WDM networks

Abstract

Channel monitoring is an essential topic for optical WDM channels. In the first part of this thesis, a novel bit error rate (BER) estimation technique based on multi-Gaussian curve fitting on amplitude histogram is proposed. Computer simulations are carried out to verify the effectiveness of the new method. The results show that the new method can achieve better accuracy in estimating BER over the conventional method especially when the signal is severely distorted. In the second part of the thesis, a novel method of channel impairments identification is proposed. The distorted amplitude histograms are characterized using X2 distance metrics. The results show that this method can effectively identify three major impairments, namely ASE noise, chromatic dispersion and inband crosstalk.