基于小波变换的MPSK符号率估计方法  

Symbol rate estimation of MPSK signals based on wavelet transform

作　　者：李小娟[1] 朱立东[1] 

机构地区：[1]电子科技大学通信抗干扰技术国家级重点实验室,四川成都611731

出　　处：《重庆邮电大学学报（自然科学版）》2010年第1期19-22,共4页Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition)

基　　金：国家自然科学基金项目资助(60872030)

摘　　要：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。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 locali- zing ability in time-domain and frequency-domain, wavelet transform has the excellent transient detection ability of the in- stants 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 （dbN） wavelet for bandlimited 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.

关 键 词：MPSK 符号率估计 小波变换 快速傅立叶变换(FFT) 

分 类 号：TN92[电子电信—通信与信息系统]