In order to transmit communication signals of different properties, quickly, effectively, and accurately, various different modulation styles can be adopted. Accurate recognition of signal modulation is required at the receive side. Automatic modulation recognition (AMR) is a key technique to identify various styles of modulation of signals received in wireless channels. It can be used in many kinds of communication systems, including single antenna system and multiple antenna system. In this paper, we propose a convolutional neural networks (CNN) aided AMR method for multiple antenna system. Compared with the high order cumulants (HOC) and artificial neural networks (ANN) aided traditional AMR classification method, both with two specific combination strategies, such as relative majority voting method and arithmetic mean method, the proposed AMR with arithmetic mean method has the best classification performance. The experimental results obtained verify that the CNN, one of the representative algorithms of deep learning, has a strong ability to exploit dominant features and classify the modulation styles.