Research on Modulation Classification of MQAM Signals Using Joint Moments

Automatic modulation classification (AMC) is a scheme to identify the data samples automatically. Usually, in wireless communication, especially through the Rayleigh fading channel, AMC performance will severe degrade. This paper presents a new method for AMC, using a modified Joint Power Estimation and modulation types of the transmitted signals by observing the receive Modulation Classification (JPEMC) algorithm. The advantage of our new algorithm is we don’t need the channel information as a priori. The Monte Carlo simulation shows that the performance of our algorithm can be better than the existing AMC algorithms.