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Cognitive radio has been proposed as an optimal solution to increase spectrum efficiency, by exploiting unused portions of radio spectrum. The first and the most important function in cognitive radio equipment, is spectrum sensing, wherein a cognitive user must sense his environment to detect a free band, then use it temporarily without causing any interference to the primary user (PU). It has been shown that the energy detection is the most chosen method, to detect the spectrum holes in the case where there is no a priori information about the PU. In this paper, we are describing tow stages architecture: The first stage is used to detect the presence of the PU with an improved energy detection technique, and the second is utilized to classify the modulation type, by combining principal component analysis to extract signal features and neural network to make the decision. Performance evaluation of our proposed architecture has been done by real word signals. 7960 A. Elrharras et al.