In this paper the negative impacts of interference transmitters on automatic modulation classification (AMC) have been discussed. We proposed two approaches for AMC in the presence of interference: single user modulation classification (SUMC) and multiuser modulation classification (MUMC). When the received power of one transmitter is larger than the other transmitters, SUMC approach recognizes the modulation type of that transmitter and other transmitters are treated as interferences. Alternatively when the received powers of all transmitters are close to each other we propose MUMC method to recognize the modulation type of all of the transmitted signals. The features being used to recognize the modulation types of transmitters for both approaches, SUMC and MUMC are higher order cumulants. The superposition property of cumulants for independent random variables is utilized for SUMC and MUMC. We investigated the robustness of our classifier with respect to different powers of the received signals via analytical and simulation results and we have shown the analytical results will be confirmed by simulations. Also we studied the effect of signal synchronization error via simulation results in the both condition for MUMC and SUMC.

We develop an algorithm for automatic recognition of digital linear modulations in the presence of interference. We utilize the superposition property of cumulants for independent random variables, to recognize the modulation type of the received signals. The proposed method benefits from the robustness of cumulant-based features to frequency offset, channel phase and phase jitter. Simulation results are provided to show the performance of our proposed classifier in the presence of interference.