A Noise Variance Optimazation Method for 2×1-Dimensional Wiener Filtered Channel Estimation

RUI Yun; LI Ming-qi; ZHANG Xiao-dong; YI Hui-yue; HU Hong-lin

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A Noise Variance Optimazation Method for 2×1-Dimensional Wiener Filtered Channel Estimation

更新时间：2025-07-16

- A Noise Variance Optimazation Method for 2×1-Dimensional Wiener Filtered Channel Estimation
- Acta Electronica Sinica Vol. 36, Issue 8, Pages: 1577-1581(2008)
- 作者机构：
  
  中国科学院上海微系统与信息技术研究所,上海,200050
- 作者简介：
- 基金信息：
- DOI：
  CLC： TN911.3TN911.6
- Published：2008
- 稿件说明：
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RUI Yun, LI Ming-qi, ZHANG Xiao-dong, et al. A Noise Variance Optimazation Method for 2×1-Dimensional Wiener Filtered Channel Estimation[J]. Acta Electronica Sinica, 2008, 36(8): 1577-1581.
DOI：

RUI Yun, LI Ming-qi, ZHANG Xiao-dong, et al. A Noise Variance Optimazation Method for 2×1-Dimensional Wiener Filtered Channel Estimation[J]. Acta Electronica Sinica, 2008, 36(8): 1577-1581. DOI：

摘要

本文提出了一种基于OFDM(Orthogonal Frequency Division Multiplexing)系统的两次一维(2×1-D)维纳滤波信道估计的噪声方差优化方法.对于2×1-D维纳滤波信道估计

维纳滤波将先后应用于频域维和时域维

而两次滤波时的噪声方差实际是不相同的

但现有的2×1-D维纳滤波信道估计方法没有考虑噪声的变化.本文首先分析出了第一次滤波后残余的噪声方差

并将其优化的结果应用于第二次滤波中

然后根据不同的优化准则对信道估计性能进行了评估.仿真结果表明

同未对噪声方差优化的信道估计方法相比

本方法具有更优的性能

且非常接近两维维纳(2-D)滤波方法.

Abstract

A noise variance optimization method is proposed for the time and frequency dimension separate (2×1-D) Wiener-filtered channel estimation of OFDM based systems.According to Wiener-filter theory

the noise variance is necessary to achieve optimal solution.For 2×1-D Wiener-filtered channel estimation

the Wiener-filtering will be applied twice respectively in time and frequency dimension.Hence

the effect of variety of noise variance induced by the first filter should be considered on the second filter in this method

but it has not been considered in the existing 2×1-D Wiener-filtered channel estimation method.This paper presents a novel algorithm which takes into account the effect of variety of noise variance.In the proposed method

the noise variance used by the second filter is optimized according to the mean square error (MSE) of channel estimation by the first filter.The exact MSE of channel estimation is derived in this paper.Moreover

the channel estimation performance is evaluated with different noise variance optimizing criteria.The simulation results show that the performance of the proposed method is better than the 2×1-D filters method without noise variance optimization

and is very close to that of the Wiener 2-dimension filter.

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