通信学报 ›› 2013, Vol. 34 ›› Issue (11): 92-100.doi: 10.3969/j.issn.1000-436x.2013.11.011

• 学术论文 • 上一篇    下一篇

稳定分布噪声下基于粒子滤波的多径时变信道盲均衡算法

夏楠1,2,邱天爽1,李景春2   

  1. 1 大连理工大学 电子信息与电气工程学部，辽宁 大连 116024
    2 国家无线电监测中心，北京 100037
  • 出版日期:2013-11-25 发布日期:2017-06-23
  • 基金资助:
    国家自然科学基金资助项目;国家自然科学基金资助项目

Particle filter-based multi-path time-varying channel blind equalization in stable noise

Nan XIA1,2,Tian-shuang QIU1,Jing-chun LI2   

  1. 1 Faculty of Electronic Information and Electrical E gineering, Dalian University of Technology, Dalian 116024, China
    2 State Radio Monitoring Center, Beijing 100037, China
  • Online:2013-11-25 Published:2017-06-23
  • Supported by:
    The National Natural Science Foundation of China;The National Natural Science Foundation of China

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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a稳定分布（SaS）噪声下对传输码元进行最大后验估计的盲贯序算法；对SaS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。

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

Abstract:

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 distribut nknown 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.

Key words: channel blind equalization, SaS particle filtering, maximum posteriori estimation, multi-path time-varying

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