华南理工大学学报(自然科学版) ›› 2010, Vol. 38 ›› Issue (5): 1-5.doi: 10.3969/j.issn.1000-565X.2010.05.001

• 电子、通信与自动控制 •    下一篇

用于MIMO-OFDM系统盲信道估计的斜投影子空间法

孙季丰 张志勇   

  1.  华南理工大学 电子与信息学院, 广东 广州 510640
  • 收稿日期:2009-06-01 修回日期:2009-07-15 出版日期:2010-05-25 发布日期:2010-05-25
  • 通信作者: 孙季丰(1964-),男,教授,主要从事通信系统的信息处理、图像与视频处理研究. E-mail:ecjfsun@scut.edu.cn
  • 作者简介:孙季丰(1964-),男,教授,主要从事通信系统的信息处理、图像与视频处理研究.
  • 基金资助:

    广东省自然科学基金资助项目(07300585)

Oblique-Projection Subspace Approach to Blind Channel Estimation of MIMO-OFDM System

Sun Ji-feng  Zhang Zhi-yong   

  1. School of Electronic and Information Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2009-06-01 Revised:2009-07-15 Online:2010-05-25 Published:2010-05-25
  • Contact: 孙季丰(1964-),男,教授,主要从事通信系统的信息处理、图像与视频处理研究. E-mail:ecjfsun@scut.edu.cn
  • About author:孙季丰(1964-),男,教授,主要从事通信系统的信息处理、图像与视频处理研究.
  • Supported by:

    广东省自然科学基金资助项目(07300585)

摘要:

为实现多输入多输出-正交频分复用(MIMO-OFDM)的盲信道估计,文中提出了斜投影子空间法,在满足算法识别系统的条件下,将接收信号空间划分为"过去"、"现在"、"将来"3个子空间,然后将"现在"子空间分别向"过去"、"将来"子空间进行斜投影,可以有效降低多径效应给接收系统带来的影响.文中给出了信道模糊矩阵的估计方法,采用了奇异值分解方法来提高算法的抗噪性能.通过与噪声子空间算法的比较,发现文中算法在牺牲少量估计精度的情况下可以大大降低计算复杂度.仿真结果表明该算法能有效地完成信道估计

关键词: 斜投影子空间法, 多输入多输出系统, 正交频分复用, 盲信道估计, 模糊矩阵

Abstract:

Proposed in this paper is an oblique-projection subspace approach to the blind channel estimation of MIMO-OFDM system,which,under conditions of satisfying the identification system,divides the signal-receiving space into three subspaces including the "past subspace",the "present subspace" and the "future subspace".By obliquely projecting the "present subspace" respectively onto the "past subspace" and the "future subspace",the impact of multi-path effect on the receiving system can be effectively eliminated.In addition,a method to estimate the ambiguous matrix of channel is proposed,and the singular value decomposition is adopted to improve the anti-noise ability of the algorithm.It is found that,as compared with the noise subspace approach,the proposed approach is of lower computational complexity only with slight sacrifice of estimation accuracy.Simulated results show the proposed projection approach is efficient for identifying system channel.

Key words: oblique-projection subspace approach, multiple-input multiple-output system, Orthogonal Frequency Division Multiplexing, blind channel estimation, ambiguous matrix