Research On Modulation Classification And Parameter Estimation Of OFDM Signal And IP Core Design

Orthogonal Frequency Division Multiplexing is widely used in the modern communication systems because of its highly anti-interference performance and highly transmission rate. Along with this, the issues of OFDM signal identification and parameter estimation would be core issues in the realms of radio frequency spectrum management, software radio technology and information countermeasure.This thesis aims at not only the low identification rate but the bad performance when the signal corrupted by multipath of existing OFDM signal identification algorithms. A novel OFDM signal identification algorithm which based on the wavelet transform is proposed. The proposed algorithm has low computational complexity and high identification accuracy which could identify the OFDM signal in AWGN and multipath environment successfully.Besides, the over sampling factor of the received signal, the parameter in time-domain of OFDM signal and the modulation type of the subcarrier are analyzed in the thesis. The estimation scheme of the over sampling factor and the time domain parameters are proposed. Furthermore, a novel modulation classification algorithm which based on the pre-processing and higher order moments is proposed to identify the modulation type of the subcarrier. The over sampling factor estimation algorithm has the advantage of low computational complexity and high estimation precise. The subcarrier modulation identification algorithm could reduce the interference inducted by the pilot signals and the virtual carriers, and could reach an outstanding performance in low SNR. The performance is evaluated and analyzed. The simulation results show that the performance of the algorithm is comparable with the existing algorithms. Last but not least, we design the IP core of OFDM identification module in the thesis.