The University of Southampton
University of Southampton Institutional Repository

Machine-learning detector based on support vector machine for 122-Gbps multi-CAP optical communication system

Machine-learning detector based on support vector machine for 122-Gbps multi-CAP optical communication system
Machine-learning detector based on support vector machine for 122-Gbps multi-CAP optical communication system
In this work, we firstly apply support vector machine (SVM) detector in 122-Gbps Multi-CAP system. It can de-map the rotated constellations directly without any correction. The concrete simulations indicate such a machine-learning based detector provides considerable BER reduction for high-density CAPs in low-frequency band, compared with hard decision.
IEEE
Sun, Lin
baf821b3-407b-4cb8-9262-14eb45f93ab7
Du, Jiangbing
244dddeb-d4c5-47ac-ab5f-24821e990586
Chen, Guoyao
77c3fcac-3128-411e-9dc4-d34880f76dc2
He, Zuyuan
150ad775-7969-49d6-8ecb-8159ada54631
Chen, Xia
64f6ab92-ca11-4489-8c03-52bc986209ae
Reed, Graham T.
ca08dd60-c072-4d7d-b254-75714d570139
Sun, Lin
baf821b3-407b-4cb8-9262-14eb45f93ab7
Du, Jiangbing
244dddeb-d4c5-47ac-ab5f-24821e990586
Chen, Guoyao
77c3fcac-3128-411e-9dc4-d34880f76dc2
He, Zuyuan
150ad775-7969-49d6-8ecb-8159ada54631
Chen, Xia
64f6ab92-ca11-4489-8c03-52bc986209ae
Reed, Graham T.
ca08dd60-c072-4d7d-b254-75714d570139

Sun, Lin, Du, Jiangbing, Chen, Guoyao, He, Zuyuan, Chen, Xia and Reed, Graham T. (2017) Machine-learning detector based on support vector machine for 122-Gbps multi-CAP optical communication system. In 2017 Opto-Electronics and Communications Conference (OECC) and Photonics Global Conference (PGC). IEEE.. (doi:10.1109/OECC.2017.8114893).

Record type: Conference or Workshop Item (Paper)

Abstract

In this work, we firstly apply support vector machine (SVM) detector in 122-Gbps Multi-CAP system. It can de-map the rotated constellations directly without any correction. The concrete simulations indicate such a machine-learning based detector provides considerable BER reduction for high-density CAPs in low-frequency band, compared with hard decision.

This record has no associated files available for download.

More information

Published date: 2017
Venue - Dates: CLEO-PR OECC & PGC 2017, Singapore, 2017-07-31 - 2017-08-04

Identifiers

Local EPrints ID: 442734
URI: http://eprints.soton.ac.uk/id/eprint/442734
PURE UUID: c4eb6203-bf71-413d-bcda-d20a8a793989
ORCID for Xia Chen: ORCID iD orcid.org/0000-0002-0994-5401

Catalogue record

Date deposited: 24 Jul 2020 16:30
Last modified: 16 Mar 2024 08:45

Export record

Altmetrics

Contributors

Author: Lin Sun
Author: Jiangbing Du
Author: Guoyao Chen
Author: Zuyuan He
Author: Xia Chen ORCID iD
Author: Graham T. Reed

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×