对称α稳定分布噪声下的Turbo均衡  

Turbo equalization in symmetric α-stable noise environments

作　　者：罗康生[1] 赵明生[1] 

机构地区：[1]清华大学电子工程系,北京100084

出　　处：《清华大学学报（自然科学版）》2010年第5期784-788,共5页Journal of Tsinghua University(Science and Technology)

基　　金：国家"八六三"高技术项目(2007AA01Z292)

摘　　要：提出了一种适用于加性对称α稳定(SαS)分布噪声环境下Turbo均衡方法。通过利用分段多项式构造较为精确地逼近SαS分布的概率密度函数,并用于最大后验概率Turbo均衡的软信息迭代过程,从而更充分地利用信道非Gauss噪声的先验统计信息。仿真结果表明:该方法在不同强度噪声情况下,误码率性能均优于Gauss噪声下的标准Turbo均衡和Chuah提出的截断Turbo均衡方法;在中等脉冲噪声情况下(α=1.5),达到10-4的误码率时信噪比Eb/N0比截断Turbo均衡方法小约2.2 dB,且与AWGN信道下卷积编码误码极限的信噪比之差约为0.8 dB。仿真结果还表明该方法具有更好的迭代收敛性能。This paper presents a turbo equalization method for the additive symmetric α-stable（SαS） noise environments.The segmented-polynomial approximation of the SαS probability distribution function was used in the maximum-a-posterior soft information iterations to fully utilize the prior information of the non-Gaussian noise.Simulations show that the method is superior to the standard Gaussian turbo method and the truncated turbo method proposed by Chuah.In moderate impulsive noise environment（α=1.5）,the signal noise rate（Eb/N0） of the method outperforms 2.2 dB,better than that of the truncated method with a bit error rate of 10-4,and about 0.8 dB far from the Eb/N0 limit in the convolution-coded AWGN channel.The results also indicate that the method has better convergence performance.

关 键 词：信道均衡 ISI信道 TURBO均衡 Α稳定分布噪声 最大后验概率算法 

分 类 号：TN911.5[电子电信—通信与信息系统]