基于小波变换的MPSK符号率估计方法

数字调制信号的参数估计是非协作通信的研究重点,符号率估计是信号调制方式识别及正确解调信号的重要参数.小波在时域和频域具有优良的局部化特征,适用于信号瞬时变化特征提取.现有的使用Haar小波的符号率估计算法中都假设码元是矩形脉冲,没有考虑实际通信系统脉冲成形滤波技术的影响.针对上述问题,在带限系统模型下,考虑了脉冲成形滤波技术对信号产生的影响,使用适合带限系统信号瞬时变化特征提取的具有高阶消失矩的Daubechies(dbN)小波,结合FFT算法,提出了一种MPSK符号率估计方法.仿真结果表明,使用该符号率估计方法要比使用Haar小波性能更优越.

Symbol rate estimation of MPSK signals based on wavelet transform

Digital modulation signal parameter estimation is an important part in the non-cooperative communication, and the symbol rate plays a key role in the modulation mode identification and signal correct demodulation. Based on the localizing ability in time-domain and frequency-domain, wavelet transform has the excellent transient detection ability of the instants when symbols changes. The existing Haar wavelet symbol rate estimation algorithms assume that the symbol is a rectangular pulse without considering the influence of pulse shaping filter. In order to solve the above problems, this paper takes into account the pulse shaping filter technology impacting on the signals, uses Daubechies (db N) wavelet for band limited communications system to extract transient characteristic of symbol change, and then estimate MPSK symbol rate with fast Fourier transform (FFT) algorithm. Simulation results show that the proposed symbol rate estimation algorithm is better than classical Haar wavelet algorithm.