SVM detection for superposed pulse amplitude modulation in visible light communications

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.