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.