摘要
提出了一种基于粒子滤波的多径时变信道盲均衡算法,并在此基础上进行扩展,提出了一种基于延迟抽样的盲均衡算法。新算法的贡献可总结为:推导出对称α稳定分布(SαS)噪声下对传输码元进行最大后验估计的盲贯序算法;对SαS分布噪声进行高斯近似并递推出信道及噪声未知参数的联合后验分布。仿真结果表明,所提出的算法是有效的,特别是在较强脉冲噪声情况下要优于其他算法。
A particle filtering (PF) based blind equalization algorithm for the multi-path time-varying channel was pre- sented and a delay sampling blind equalization algorithm was proposed. The contribution of the novel algorithm can be summarized as follows: the blind sequential algorithm was derived which performs the maximum a posteriori (MAP) symbol detection in symmetric-alpha-stable (SaS) distribution noise; and the joint posterior distribution of the Gaussian approximation for SaS distribution noise and the joint posterior distribution of the unknown channel and noise parameters were derived and presented. The simulation results demonstrate that the proposed method is valid and outperforms the existing algorithms, especially in the case of strong impulsive noise.
出处
《通信学报》
EI
CSCD
北大核心
2013年第11期92-99,共8页
Journal on Communications
基金
国家自然科学基金资助项目(61139001
61172108)~~
关键词
信道盲均衡
SaS粒子滤波
最大后验估计
多径时变信道
channel blind equalization
SaS particle filtering
maximum posteriori estimation
multi-path time-varying