基于历史信息的软卡尔曼滤波迭代时变信道估计方法

doi:10.11959/j.issn.1000-0801.2020038

电信科学 ›› 2020, Vol. 36 ›› Issue (9): 23-31.doi: 10.11959/j.issn.1000-0801.2020038

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

南京邮电大学江苏省无线通信重点实验室，江苏南京 210003

修回日期:2020-08-17 出版日期:2020-09-20 发布日期:2020-09-27
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
基金资助:
江苏省自然科学基金面上研究项目(BK20191378);江苏省高等学校自然科学研究项目(18KJ13510034);第11批中国博士后科学基金特别资助项目(2018T110530);国家自然科学基金资助项目(61401232);国家自然科学基金资助项目(61671251);国家自然科学基金资助项目(61771255)

Historical information based iterative soft Kalman time-varying channel estimation method

Lu CHENG,Lihua YANG(),Zenghao WANG,Jie ZHANG,Yan LIANG

Jiangsu Key Laboratory of Wireless Communication,Nanjing University of Posts and Telecommunications,Nanjing 210003,China

Revised:2020-08-17 Online:2020-09-20 Published:2020-09-27
Supported by:
The Natural Science Foundation Program of Jiangsu Province(BK20191378);The National Science Research Project of Jiangsu Higher Education Institutions(18KJ13510034);The 11th batch of China Postdoctoral Science Fund Special Funding Project(2018T110530);The National Natural Science Foundation of China(61401232);The National Natural Science Foundation of China(61671251);The National Natural Science Foundation of China(61771255)

摘要/Abstract

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。

关键词: MIMO-OFDM, 高速移动, 时变信道估计, 历史信息, 软卡尔曼滤波, 迭代信道估计

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.

Key words: MIMO-OFDM, high-speed mobility, time-varying channel estimation, historical information, soft-Kalman filter, iterative channel estimation

中图分类号:

TN929

程露,杨丽花,王增浩,张捷,梁彦. 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,Jie ZHANG,Yan LIANG. Historical information based iterative soft Kalman time-varying channel estimation method[J]. Telecommunications Science, 2020, 36(9): 23-31.

图/表 4

图1

图2

图3

表1

不同信道估计方法的复杂度比较"

信道估计方法	总计算复杂度
参考文献[7]	$N^{2} L + 2 N_{p} Q^{2} + N_{p} Q + o (Q^{3})$
参考文献[6]	$L [4 N Q^{2} + N^{2} Q + Q^{3} + 2 o (Q^{3})] + 2 N [Q^{2} L N (8 N - 1) + 3]$
本文所提方法	$N^{2} L + [4 N Q^{2} + N^{2} Q + Q^{3} + 2 o (Q^{3})] + 2 N [Q^{2} L N (8 N - 1) + 3]$

表1

参考文献 20

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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

Historical information based iterative soft Kalman time-varying channel estimation method

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