一种适用于强脉冲噪声下的对数型恒模盲均衡算法

A Logarithmic-type Constant Modulus Blind Equalization Algorithm for Strong Impulsive Noise

针对脉冲噪声下恒模算法(Constant Modulus Algorithm,CMA)失败的问题,通过分析脉冲噪声的影响,提出了一种基于最小均方(Least Mean Square,LMS)准则的对数型恒模算法(Logarithmic-type CMA,LT-CMA)。LT-CMA利用对数函数的非线性变换特性自适应地抑制强脉冲噪声对误差函数的影响,并且利用l2-范数进行信号归一化处理以增强算法的稳健性。仿真结果表明,所提出的LT-CMA可以适应于高斯噪声环境和脉冲噪声环境;与经典自适应均衡算法相比,在收敛速度和稳健性两方面上,所提出的LT-CMA都有显著的提升。

For the failure of constant modulus algorithm(CMA) for impulse noise,a logarithmic-type CMA(LT-CMA) is proposed based on least mean square(LMS) error criterion after analyzing influence of the impulse noise. It takes advantage of the characteristic of nonlinear transformation of the logarithmic function to adaptively suppress impact of the impulse noise on error function. Also, it uses the l 2-norm to normalize the signals in order to enhance its robustness. Simulation results show that the proposed LT-CMA not only adapts to Gaussian noise environment but also impulse noise environment. Compared with some classical adaptive algorithms, the proposed LT-CMA can achieve a great improvement in convergence speed and robustness.