Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/6013
Title: Modulation format identification in heterogeneous fiber-optic networks using artificial neural networks
Authors: Khan, FN
Zhou, Y
Lau, APT 
Lu, C 
Keywords: Coherent communications
Fiber optics communications
Fiber optics links and subsystems
Optical communications
Issue Date: 21-May-2012
Publisher: Optical Society of America
Source: Optics express, 21 May 2012, v. 20, no. 11, p. 12422-12431 How to cite?
Journal: Optics express 
Abstract: We propose a simple and cost-effective technique for modulation format identification (MFI) in next-generation heterogeneous fiber-optic networks using an artificial neural network (ANN) trained with the features extracted from the asynchronous amplitude histograms (AAHs). Results of numerical simulations conducted for six different widely-used modulation formats at various data rates demonstrate that the proposed technique can effectively classify all these modulation formats with an overall estimation accuracy of 99.6% and also in the presence of various link impairments. The proposed technique employs extremely simple hardware and digital signal processing (DSP) to enable MFI and can also be applied for the identification of other modulation formats at different data rates without necessitating hardware changes.
URI: http://hdl.handle.net/10397/6013
ISSN: 1094-4087 (eISSN)
DOI: 10.1364/OE.20.012422
Rights: ©2012 Optical Society of America
This paper was published in Optics Express and is made available as an electronic reprint with the permission of OSA. The paper can be found at the following URL on the OSA website: http://dx.doi.org/10.1364/OE.20.012422. Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law.
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