引入动量项的正交小波变换盲均衡算法

针对常数模算法(CMA)收敛速度慢的缺点,推导了均衡器的正交小波表示式及正交变换矩阵的表示式,在分析正交小波变换常数模盲均衡算法(WTCMA)的基础上,将动量算法引入WTCMA中,得到了一种引入动量项的正交小波变换常数模盲均衡新算法(MWTCMA).该算法将基于小波变换的常数模盲均衡算法和动量项相结合,通过归一化的正交小波变换和引入动量项来提高收敛速度.同时给出了算法的收敛条件,并对算法计算量进行了分析.水声信道仿真结果表明:与基于正交小波变换的常数模盲均衡算法(WTCMA)及常规常数模算法(CMA)相比,新算法具有更快的收敛速度,从而能更有效地实现信号与噪声的分离以及信号的实时恢复.

Momentum Term and Orthogonal Wavelet-based Blind Equalization Algorithm

Aiming at the slow convergence rates of Constant Modulus Algorithm (CMA), the expression of the equalizer with orthogonal Wavelet and orthogonal wavelet transform matrix was deduced. Through analyzing orthogonal Wavelet Transform-based CMA (WTCMA) and introducing momentum algorithm into WTCMA, a new Momentum term and orthogonal Wavelet Transform-based CMA(MWTCMA) was proposed. In this proposed algorithm, WTCMA was combined with momentum term, and the convergence rates of the proposed algorithm could be improved by normalizing orthogonal wavelet transform and adding to the momentum term. At the same time, the convergence condition and the computational quantity of the proposed algorithm were studied. Simulation tests with underwater acoustic channel indicate that the convergence rates of the proposed algorithm are faster than those of the CMA and the WTCMA. Accordingly, MWTCMA has better the performance of real time information retrieval and practicability.