非高斯噪声下基于有界非线性函数的快速盲均衡方法  

Fast Blind Equalization based on Bounded Non-linear Function under Non-Gaussian Noise

作　　者：王壮[1] WANG Zhuang(Nanjing University of Posts and Telecommunications,Nanjing Jiangsu 210000,China)

机构地区：[1]南京邮电大学,江苏南京210000

出　　处：《通信技术》2020年第7期1606-1611,共6页Communications Technology

摘　　要：盲均衡技术广泛应用于通信系统中以消除符号间干扰。支持非高斯噪声环境下的盲均衡方法仍然是一个挑战。为了提高它的收敛速度和鲁棒性,提出了一种利用有界非线性函数(Bounded Nonlinear Function,BNF)和拟牛顿法的快速盲均衡方法。首先,提出一种基于BNF的代价函数,有效消除非高斯噪声,实现均衡。其次,采用拟牛顿法作为迭代方法,加快收敛速度。理论分析表明,该算法具有较强的收敛性能。仿真结果也表明,该方法在非高斯噪声下收敛速度快,鲁棒性好。Blind equalization is widely used in communication systems to eliminate inter-symbol interference.Supporting blind equalization methods in non-Gaussian noise environments is still a challenge.In order to improve its convergence speed and robustness,a fast blind equalization method using BNF(Bounded Nonlinear Function)and quasi-Newton method is proposed.Firstly,a cost function based on BNF is proposed to effectively eliminate non-Gaussian noise and achieve equalization.Then,the quasi-Newton method is adopted as the iterative method to accelerate the convergence speed.Theoretical analysis shows that this algorithm has fairly strong convergence performance.Simulation results indicate that this method has fast convergence speed and good robustness under non-Gaussian noise.

关 键 词：盲均衡 有界非线性函数(BNF) 拟牛顿 非高斯噪声 

分 类 号：TN929.53[电子电信—通信与信息系统]