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Nowadays there are different modulation types that are used in various digital communication systems such as surveillance and control of communication systems, so that the need to find efficient methods for their discrimination becomes a necessity. In this paper, we discuss two algorithms which are used for the automatic modulation classification: the Average Likelihood Ratio Test (ALRT) and the Joint Power Estimation and Modulation Classification (JPEMC). These approaches can be used to classify many types of modulations signals: M-PSK, M-QAM, M-FSK…First of all, we present the two algorithms to recognize automatically the type of the modulated signals. In the second part, we compare their performance for a variety of modulation types. Simulations experiments are illustrated under Gaussian cannel.

systems that enables us to identify the corresponding wireless network. This paper reviews an approach for the automatic There are various parameters to ensure the OFDM orthogonal frequency division multiplexing (OFDM) systems classification which are essentially frequency signals classification for the cognitive radio applied to the band, modulation, cyclic prefix [2] [3], subcarriers standard IEEE 802.11 (the WiFi: Wireless Fidelity