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; 邱天爽; 李景春

doi:10.3969/j.issn.1000-436x.2013.11.011

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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

学术论文

- 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
- Particle filter-based multi-path time-varying channel blind equalization in stable noise
- 通信学报 2013年34卷第11期页码：92-100
- 作者机构：
  
  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
- 作者简介：
  
  [ "夏楠（1983-），男，辽宁大连人，博士，国家无线电监测中心工程师，主要研究方向为通信信号监测与信息处理等。" ]
  [ "邱天爽（1954-），男，江苏海门人，博士，大连理工大学教授、博士生导师，主要研究方向为信号信息处理。" ]
  [ "李景春（1966-），男，河北宁晋人，博士，国家无线电监测中心副主任兼总工程师，主要研究方向为无线电监测理论与应用。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61139001);国家自然科学基金资助项目(61172108)
- DOI：10.3969/j.issn.1000-436x.2013.11.011
  中图分类号： TN911.72
- 网络出版日期：2013-11，
  
  纸质出版日期：2013-11-25
- 稿件说明：
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夏楠, 邱天爽, 李景春. 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[J]. 通信学报, 2013,34(11):92-100.

Nan XIA, Tian-shuang QIU, Jing-chun LI. Particle filter-based multi-path time-varying channel blind equalization in stable noise[J]. Communication journal, 2013, 34(11): 92-100.
夏楠, 邱天爽, 李景春. 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[J]. 通信学报, 2013,34(11):92-100. DOI： 10.3969/j.issn.1000-436x.2013.11.011.

Nan XIA, Tian-shuang QIU, Jing-chun LI. Particle filter-based multi-path time-varying channel blind equalization in stable noise[J]. Communication journal, 2013, 34(11): 92-100. DOI： 10.3969/j.issn.1000-436x.2013.11.011.

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。

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.

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references

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