Method of square QAM signals recognition

By combining the traditional signal processing tool-FFT with wavelet transform,a new method of baud-rate extraction for QAM signal is put forward in this paper.

Analysis and simulation results demonstrate that compared with conventional blind qualization algorithms,the proposed algorithm provides superior performace by increasing the convergence rate and decreasing the steady-state mean square error,which is more efficient for blind demodulation for high-order QAM signal.

This paper is focusing on study of NDA nonlinear least-squares(NLS) carrier frequency offset estimation for QAM signals.

This paper deduces the NDA SNR estimation algorithm for QAM signals in additive Gaussian white noise channel and on the condition of the equivalent a priori probability of transition signals positioning on every constellation point by using statistics.

The Recognition of QAM Signal Based on Constellation Diagram;

Blind Estimation of Star-QAM Carrier Frequency over Frequency-selective Fading Channels;