基于最小差错概率的变步长盲均衡算法及仿真

The Simulation of Blind Equalization Algorithm Based on Minimum Error Probability of Variable Step Size

在分析了李道本、陈少霞提出的基于最小差错概率盲均衡算法的基础上,用牛顿梯度变步长实现了基于最小差错概率新的盲均衡算法,仿真结果表明,与固定步长的盲均衡算法相比,该算法收敛速度快,均方误差小,在均衡技术的应用方面有一定的实用价值.

This paper analyzes minimum error probability blind equalization algorithm proposed by Daoben Li and shaoxia Chen. A new minimum error probability blind equalization based on Newton gradient steepest ascent variable step size algorithm is proposed and the result shows that it＇ s faster convergence and steady smaller MSE than fixed step size algorithm. It is valuable for the equalization technology.