计算机应用 ›› 2015, Vol. 35 ›› Issue (11): 3265-3269.DOI: 10.11772/j.issn.1001-9081.2015.11.3265

• 网络与通信 • 上一篇    下一篇

基于正交频分复用的线性最小均方误差信道估计改进算法

谢斌, 陈博, 乐鸿浩   

  1. 江西理工大学 信息工程学院, 江西 赣州 341000
  • 收稿日期:2015-06-03 修回日期:2015-07-09 发布日期:2015-11-13
  • 通讯作者: 谢斌(1977-),男,江西赣州人,副教授,硕士,主要研究方向:信号处理、信息安全.
  • 作者简介:陈博(1989-),男,河南郑州人,硕士研究生,主要研究方向:电子与通信工程; 乐鸿浩(1990-),男,江西抚州人,硕士研究生,主要研究方向:电子与通信工程.
  • 基金资助:
    国家自然科学基金资助项目(61363076);江西省自然科学基金资助项目(20142BAB207020).

Improved linear minimum mean square error channel estimation algorithm based on orthogonal frequency division multiplexing

XIE Bin, CHEN Bo, LE Honghao   

  1. Faculty of Information Engineering, Jiangxi University of Science and Technology, Ganzhou Jiangxi 341000, China
  • Received:2015-06-03 Revised:2015-07-09 Published:2015-11-13

摘要: 传统的线性最小均方误差(LMMSE)信道估计要求已知信道的统计特性,而实际应用中无线信道的统计特性往往是不可知的.针对无线信道的不确定性,根据时域信道上能量分布的稀疏性特点,在最小二乘(LS)算法的基础上提出了一种改进的LMMSE信道估计算法.该算法从当前信道置信度较高的频率响应出发,把相邻子载波信道估计误差的比值作为信道响应的加权系数,然后通过加权平均的方法计算出多径信道下的信道响应.该算法避免了繁琐的矩阵求逆与分解运算,能够有效降低算法复杂度.实验结果表明,所提算法总体性能优于LS算法及经过奇异值分解的线性最小均方误差(SVD-LMMSE)估计算法,且其误码率接近于传统的LMMSE算法.

关键词: 正交频分复用, 信道估计, 无线信道, 均方误差, 误码率

Abstract: Traditional Linear Minimum Mean Square Error (LMMSE) channel estimation was required to know the statistical characteristics of the channel. However, these characteristics are usually unknown in practical applications. Aiming at the uncertainty of wireless channel statistics, taking the time-domin channel sparsity of the energy distribution into consideration, this article proposed an improved LMMSE channel estimation algorithm based on Least Squares (LS) estimation. The algorithm began with the highest confidence degree subcarrier, making the adjacent subcarrier channel estimation value as the current subcarrier real response to compute the weighting coefficient, then to complete channel response of the multiple channels by the method of weighted average. This algorithm avoided the complicated operation of the matrix inversion and decomposition, and might be done effectively and easily. The experimental results show that the performance of the improved algorithm is better than LS and the SVD-LMMSE (Singular Value Decomposition-Linear Minimum Mean Square Error) channel estimation, and the Bit Error Ratio (BER) is close to traditional LMMSE algorithm.

Key words: Orthogonal Frequency Division Multiplexing (OFDM), channel estimation, wireless channel, Mean Square Error (MSE), Bit Error Ratio (BER)

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