通信学报 ›› 2007, Vol. 28 ›› Issue (2): 23-28.doi: 1000-436X(2007)02-0023-06

• 学术论文 • 上一篇    下一篇

基于导频和修正Kalman滤波的MIMO-OFDM信道估计方法

宋铁成,尤肖虎,沈连丰,宋晓晋   

  1. 东南大学 移动通信国家重点实验室,江苏 南京210096
  • 出版日期:2007-02-25 发布日期:2017-08-03
  • 基金资助:
    国家自然科学基金资助项目;江苏省自然科学基金资助项目;江苏省高技术研究开发项目

Channel estimation method for MIMO-OFDM systems based on pilots and modified Kalman filter

Tie-cheng SONG,Xiao-hu YOU,Lian-feng SHEN,Xiao-jin SONG   

  1. National Mobile Communications Research Laboratory,Southeast University,Nanjing 210096,China
  • Online:2007-02-25 Published:2017-08-03
  • Supported by:
    The National Natural Science Foundation of China;The Natural Science Foundation of Jiangsu Province;The High Technology Research and Development Program of Jiangsu Province

摘要:

提出了一种适用于时间频率选择性衰落信道的MIMO-OFDM 系统的组合信道估计方法。采用 AR 过程对信道进行建模,利用基于导频的低维Kalman滤波算法进行信道估计,并采用LS算法估计时变的信道衰减因子。Kalman滤波跟踪了信道的时域相关性,为了同时跟踪信道的频域相关性,采用了一种基于MMSE (minimum mean square error)的合并器对Kalman滤波算法进行修正。仿真表明,提出的这种组合算法降低了传统的Kalman滤波结构的复杂度,能够跟踪信道的时频变化,改进了基于LS准则的信道估计算法,并且与复杂的高维Kalman滤波

关键词: MIMO-OFDM, 信道估计, Kalman, LS, MMSE合并器

Abstract:

A combined channel estimation method of time-frequency-selective fading channels in MIMO-OFDM systems was proposed.The time-varying channel was modeled as an autoregressive (AR) process and a low-dimensional Kalman filter based on pilots was used to estimate the AR parameters,and the LS(least square) algorithm was adopted to track the time-varying channel fading factors.The Kalman estimator explored the time-domain correlation of the channel,and a minimum mean square error (MMSE) combiner was used to modify the Kalman estimates.The proposed solution could reduce the complexity of the high-dimensional Kalman filter and track the channel both in frequency and time domains.The simulation results show that this method improves the LS estimates and has a comparable performance to the complex high-dimensional Kalman channel estimation method.

Key words: MIMO-OFDM, channel estimate, Kalman, least square, MMSE combiner

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