Experimental demonstration of a cognitive quality of transmission estimator for optical communication systems

Publication: Research - peer-reviewJournal article – Annual report year: 2012

Documents

DOI

View graph of relations

The impact of physical layer impairments in optical network design and operation has received significant attention in the last years, thereby requiring estimation techniques to predict the quality of transmission (QoT) of optical connections before being established. In this paper, we report on the experimental demonstration of a case-based reasoning (CBR) technique to predict whether optical channels fulfill QoT requirements, thus supporting impairment-aware networking. The validation of the cognitive QoT estimator is performed in a WDM 80 Gb/s PDM-QPSK testbed, and we demonstrate that even with a very small and not optimized underlying knowledge base, it achieves between 79% and 98.7% successful classifications based on the error vector magnitude (EVM) parameter, and approximately 100% when the classification is based on the optical signal to noise ratio (OSNR).
Original languageEnglish
JournalOptics Express
Publication date2012
Volume20
Issue26
PagesB64-B70
ISSN1094-4087
DOIs
StatePublished

Conference

Conference38th European Conference and Exhibition on Optical Communication
CountryNetherlands
CityAmsterdam
Period16/09/1220/09/12
Internet addresshttp://www.ecoc2012.org/

Bibliographical note

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://www.opticsinfobase.org/oe/abstract.cfm?uri=oe-20-26-B64. Systematic or multiple reproduction or distribution to multiple locations via electronic or other means is prohibited and is subject to penalties under law.

CitationsWeb of Science® Times Cited: 3
Download as:
Download as PDF
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
PDF
Download as HTML
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
HTML
Download as Word
Select render style:
APAAuthorCBEHarvardMLAStandardVancouverShortLong
Word

Download statistics

No data available

ID: 35965425