J4 ›› 2009, Vol. 36 ›› Issue (3): 553-556.

• 研究论文 • 上一篇    下一篇

迭代的叠加训练序列信道估计技术

师哲   

  1. (1. 中国科学院 西安光学精密机械研究所 瞬态光学与光子技术国家重点实验室,陕西 西安  710119;
    2. 中国科学院 研究生院,北京  100039)
  • 收稿日期:2008-02-28 修回日期:2008-04-09 出版日期:2009-06-20 发布日期:2009-07-04
  • 基金资助:

    中国科学院“百人计划”项目资助

Iterative channel estimator using superimposed training

SHI Zhe   

  1. (1. State Key Lab. of Transient Optics and Photonics, Xi'an Inst. of Optics and Precision Mechanics, Chinese Academy of Sci., Xi'an  710119, China;
    2. Graduate School of the Chinese Academy of Sciences, Beijing  100039, China)
  • Received:2008-02-28 Revised:2008-04-09 Online:2009-06-20 Published:2009-07-04

摘要:

在基于叠加训练序列信道估计的基础上,提出了一种新的信道估计算法,在接收机端利用阈值判决对数据估计精度提高,使用接收数据和信道估计的初始值进行迭代运算,可进一步提高估计的精度.计算机仿真表明,经过3~4次迭代运算后,估计的均方误差和误码率在信噪比为15 dB时都降低了一个数量级,表明了算法的有效性.

关键词: 信道估计, 叠加训练序列, 多径信道, 一阶统计量

Abstract:

Because of high bandwidth efficiency and low complexity, channel estimation based on superimposed training (ST) has received wide considerations in recent years. In this paper, a new iterative method for channel estimation is proposed based on the ST method. Using the improvement from symbol estimation after thresholding, received sequences and estimation of channel state information are used to do iterative computation in the receiver. Computer simulations show that the mean square error (MSE) and bit error rate (BER) can be reduced by an order of magnitude with the signal-to-noise ratio around 15 dB after 3~4 iterations.

Key words: channel estimation, superimposed training, multipath channels, first order statistics

中图分类号: 

  • TN911.7