基于历史信息的软卡尔曼滤波迭代时变信道估计方法

程露; 杨丽花; 王增浩; 张捷; 梁彦

doi:10.11959/j.issn.1000-0801.2020038

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基于历史信息的软卡尔曼滤波迭代时变信道估计方法

研究与开发 | 更新时间：2024-06-05

- 基于历史信息的软卡尔曼滤波迭代时变信道估计方法
- Historical information based iterative soft Kalman time-varying channel estimation method
- 电信科学 2020年36卷第9期页码：23-31
- 作者机构：
- 作者简介：
  
  [ "程露（1995- ），女，南京邮电大学通信与信息学院硕士生，主要研究方向为移动通信" ]
  [ "杨丽花（1984- ），女，南京邮电大学副教授，主要研究方向为移动无线通信、通信信号处理、多载波通信系统等" ]
  [ "王增浩（1994- ），男，南京邮电大学通信与信息学院硕士生，主要研究方向为移动通信" ]
  [ "张捷（1996- ），女，南京邮电大学通信与信息学院硕士生，主要研究方向为宽带移动通信" ]
  [ "梁彦（1979- ），女，南京邮电大学副教授，主要研究方向为宽带无线通信、通信信号处理等" ]
- 基金信息：
  
  江苏省科技厅自然科学基金资助项目;The National Science Foundation Program of Jiangsu Province(BK20191378);江苏省高等学校自然科学研究面上项目;The National Science Research Project of Jiangsu Higher Education Institutions(18KJ13510034);第11批中国博士后科学基金特别资助项目;The 11th Batch of China Postdoctoral Science Fund Special Funding Project(2018T110530);国家自然科学基金资助项目;The National Natural Science Foundation of China(61401232);国家自然科学基金资助项目;The National Natural Science Foundation of China(61671251);国家自然科学基金资助项目;The National Natural Science Foundation of China(61771255)
- DOI：10.11959/j.issn.1000-0801.2020038
  中图分类号： TN929
- 网络出版日期：2020-09，
  
  纸质出版日期：2020-09-20
- 稿件说明：
移动端阅览
程露, 杨丽花, 王增浩, 等. 基于历史信息的软卡尔曼滤波迭代时变信道估计方法[J]. 电信科学, 2020,36(9):23-31.

Lu CHENG, Lihua YANG, Zenghao WANG, et al. Historical information based iterative soft Kalman time-varying channel estimation method[J]. Telecommunications science, 2020, 36(9): 23-31.
程露, 杨丽花, 王增浩, 等. 基于历史信息的软卡尔曼滤波迭代时变信道估计方法[J]. 电信科学, 2020,36(9):23-31. DOI： 10.11959/j.issn.1000-0801.2020038.

Lu CHENG, Lihua YANG, Zenghao WANG, et al. Historical information based iterative soft Kalman time-varying channel estimation method[J]. Telecommunications science, 2020, 36(9): 23-31. DOI： 10.11959/j.issn.1000-0801.2020038.

摘要

针对高速移动MIMO-OFDM系统，提出了一种基于历史信息的软卡尔曼滤波迭代时变信道估计方法。考虑高速铁路环境中不同列车在相同位置处的信道具有很强的相关性，首先利用历史列车的信道信息获取最优基函数，基于该基函数对信道建模，将对信道的估计转换成基系数的估计，降低了计算复杂度和提高了信道估计精度。其次，在每次迭代中采用了软卡尔曼滤波和数据检测联合的方法估计基系数；为了更好地减少数据检测误差传播的影响，采用软数据检测方法，并且在每次迭代中将软数据检测误差作为噪声进行处理。另外，采用的软卡尔曼滤波器不涉及 AR 模型跟踪因子，避免了估计跟踪因子引入的计算复杂度。仿真结果表明，所提方法具有更好的估计性能，且更适用于实际的高速移动场景的时变信道获取。

Abstract

For high-speed mobile MIMO-OFDM systems

a historical information based iterative soft-Kalman filter time-varying channel estimation method was proposed.Considering that the channels experienced by different trains in the high-speed railway environment have strong correlation

the channel information of the historical train was firstly used to obtain the optimal basis function

which can be employed to model the channel.By the optimal basis function

the computational complexity was reduced and the channel estimation accuracy was improved for the proposed method.Secondly

the soft-Kalman filter and data detection were jointed to estimate the base coefficient in each iteration.To reduce the effect of data detection error propagation on the channel estimation

the soft data detection scheme was employed and the soft detection error was treated as noise in each iteration.In addition

the soft-Kalman filter used in the proposed method does not involve the AR model tracking factor

thereby avoiding the computational complexity introduced by the estimated tracking factor.The simulation results show that the proposed method has better estimation performance

and is more suitable for time-varying channel acquisition of actual high-speed mobile scenarios.

关键词

Keywords

references

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