量化在基于正交小波的盲均衡算法上的应用

Application of quantification to orthogonal wavelet based CMA blind equalization

常数模算法(CMA)是实际中应用最广的一种盲均衡算法.基于正交小波的CMA算法(WBCMA)与传统的LMS算法的横向均衡器相比收敛速度快,但计算量却有所增加.把量化应用到WBCMA上,采用以2的整数次幂对误差项进行量化,减小了误差项的字节数,因此减少了算法迭代中的乘法运算.计算机仿真证明了该方法的有效性.

Adaptive blind equalization has gained widely spread use in communication receivers operating without training signals. In particular, the Constant Modulus Algorithm (CMA) has become a favorite of practitioners. The orthogonal wavelet based CMA blind equalization converges faster than the traditional LMS algorithms, but its cost is the increase in computational complexity. This paper applies quantification to WBCMA by using the integral power of 2 to quantify the error term. The bit of error term is decreased. Thereby, there is much reduction in computational complexity. Computer simulation proves the validity of this algorithm.