Performance improvement of blind classification of digital modulations

Abstract

Blind modulation classification finds extensive applications in military and civilian areas There is a need for improvement of the existing modulation classification methods in adverse channel conditions which is the motivation for this research The likelihood based method is adopted due to the availability of the optimum solution In a non data aided scenario blind parameter estimation becomes the essential preprocessing stage for the likelihood based modulation classification In this rese