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为了进一步提高CMA盲均衡算法的收敛速度和均衡性能,研究了一种变步长常数模盲均衡算法。常数模盲均衡算法中,步长参数直接影响算法的收敛速度和均衡性能,合理的选择步长参数不仅能够避免算法发散或收敛过慢,并且适时调整步长参数可以避免算法陷入局部极小值。高阶均方误差直接反映算法的收敛状态,所以可以利用高阶均方误差作为步长参数的调整因子。计算机仿真表明以高阶均方误差作为步长参数调整因子使常数模盲均衡算法具有了更快的收敛速度和更好的均衡效果。
In order to further improve the convergence rate and equalization performance of CMA blind equalization algorithm, a variable step constant modulus blind equalization algorithm is studied. In the constant modulus and blind equalization algorithm, the step size parameter directly affects the convergence speed and equalization performance of the algorithm. The reasonable choice of the step size parameter can not only avoid divergence or slow convergence of the algorithm, but also adjust the step size parameter in time to prevent the algorithm from falling into a local minimum value. The high-order mean square error directly reflects the convergence state of the algorithm, so high-order mean square error can be used as the adjustment factor of the step size parameter. Computer simulation shows that the high-order mean square error as a step parameter adjustment factor makes the constant modulus blind equalization algorithm have faster convergence speed and better equalization effect.