基于最大后验估计的自适应盲均衡算法

MAP-based adaptive blind equalization algorithm

为了减小最大后验概率(MAP)盲均衡算法中稳态误差和收敛速度,提出了一种改进的基于最大后验估计的盲均衡算法。运用不等概思想改进自适应σ的MAP盲均衡算法,得到了基于概率和自适应σ的MAP盲均衡算法。定量分析和仿真结果表明改进算法和MAP的盲均衡算法相比,稳态调整量的理论值更小,稳态剩余根均方误差值小于MAP盲均衡算法,收敛速度快于MAP盲均衡算法。

To reduce the residual root mean square error（RMSE） and convergence speed in maximum a posteriori（MAP）,an improved blind equalization algorithm based on MAP estimation is presented.The idea of unequal probability is used to improve MAP algorithm with adaptive σ.Quantitative analysis and simulation result shows that improved algorithms have smaller theoretical value of steady-state adjustment and residual RMSE,faster convergence speed.