基于最大熵密度近似技术的16-QAM盲均衡算法

16QAM Blind Equalization via Maximum Entropy Density Approximation Technique

提出了基于最大熵密度近似技术的16-QAM盲均衡算法以提高均衡性能。通过分析和计算机仿真,比较了16-QAM在不同算法下的均衡性能。仿真结果表明,处理复杂信道(ISI值较高)以及高信噪比信道时,采用从非线性方程获得的新的拉格朗日乘数,收敛速度更快。

A new blind equalization method was proposed for the16QAM constellation input inspired by the maximum entropy density approximation technique with improved equalization performance.It compared with different algorithms through analysis and computer simulation.Simulation results indicate that when we deal with a difficult channel(where the initial ISI is considered as very high)and high SNR case,a much faster convergence rate is obtained when using the Lagrange multipliers from the nonlinear equation for the Lagrange multipliers instead of those calculated from the linear part.