基于修正常系数模板的变步长双模式盲自适应均衡算法

Variable Step, Dual Mode Blind Adaptive Equalization Algorithm Based on Modified Constant Modulus

为解决修正常系数模板算法(MCMA)收敛速度缓慢的问题,在MCMA算法的基础上,给出了一种变步长双模式MCMA算法.改进算法在启动阶段用步长可变加快其收敛性,在收敛后转换到判决引导模式(DD),以保证算法收敛后稳态误差在可靠范围内.通过对实测信道的Monte-Carlo仿真,比较了MCMA算法和变步长双模式MCMA算法的性能,证明了该改进算法收敛速度快,稳态误差小.

To solve the problem of slow convergence in the modified constant modulus algorithm (MCMA), a variable step and dual mode blind equalization algorithm is proposed, based on the MCMA algorithm. The proposed algorithm uses a variable step size in it's start-up to speed up its convergence, and switches it self to a decision directed (DD) mode after it has been converged to keep the error in a robust state and stay in a reliable bound. The performances of the proposed algorithm and the original one are compared by Monte-Carlo simulation, in which channel data measured on practice is used. Simulation demonstrates that the proposed algorithm converges faster and gives out a smaller error in its steady state.