This paper proposes a scheme for identification and classification of Orthogonal Frequency Division Multiple Access (OFDMA) signals. Specifically, the cyclostationary pilot signature of an IEEE 802.16e standard compliant waveform is investigated. The proposed scheme performs waveform identification through a preamble cross-correlation technique. Classification is achieved through the use of a pilot cross-correlation technique in combination with cyclostationary feature extraction in order to determine the cyclic prefix of the IEEE 802.16e waveform. Similar methods are then used for determining other OFDMA waveform parameters, such as the FFT size, Segment number and IDcell. MATLAB simulation results validate the preamble cross-correlation and pilot cross-correlation techniques as effective methods of signal identification and classification, respectively.