Likelihood ratio tests for modulation classification

We discuss modulation classification (MC) algorithms that are based on the decision theoretic approach, where the MC problem is viewed as a multiple-hypothesis testing problem. In particular, a random-phase AWGN channel is considered and possible solutions to this hypothesis testing problem are reviewed. We present two novel algorithms and we compare their performance with existing ones for a variety of modulation pairs. Simulation results show that these new algorithms can offer a significant performance gain for classification of dense, non-constant envelope constellations.