Identification and Classification of Orthogonal Frequency Division Multiple Access (OFDMA) Signals Used in Next Generation Wireless Systems

This thesis explores identification and classification of Orthogonal Frequency Division Multiple Access based signals and proposes a scheme to achieve this goal. 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 an algorithm called the fast Fourier transform accumulation method that performs 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. The proposed scheme is implemented with MATLAB simulation code and the significant results of the simulation are presented and discussed. The MATLAB simulation validated the preamble cross-correlation process and the pilot cross-correlation technique in conjunction with the fast Fourier transform accumulation method as effective methods of signal identification and classification, respectively. The original document contains color images.