SVM detection for superposed pulse amplitude modulation in visible light communications

Youli Yuan, Min Zhang, Pengfei Luo, Zabih Ghassemlooy, Danshi Wang, Xiongyan Tang, Dahai Han

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

10 Citations (Scopus)

Abstract

A support vector machine (SVM)-based data detection for 8-superposed pulse amplitude modulation in visible light communication is proposed and experimentally demonstrated. In this work, the SVM detector contains three binary classifiers with different classification strategies. And the separating hyperplane of each SVM is constructed by training data. The experiment results show that the SVM detection offers 35% higher data rates when compared with the traditional direct decision method.
Original languageEnglish
Title of host publicationProceedings of the 2016 10th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)
Place of PublicationPiscataway
PublisherIEEE
Pages1-5
ISBN (Print)9781509025268
DOIs
Publication statusPublished - 22 Sep 2016
Event10th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP 2016) - Prague
Duration: 22 Sep 2016 → …

Conference

Conference10th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP 2016)
Period22/09/16 → …

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