基于后验加权更新的OFDM/FBMC双选择性信道全矩阵估计方法

杨黎明; 杨坤; 陈樑

doi:10.11959/j.issn.1000-0801.DXKX260191

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基于后验加权更新的OFDM/FBMC双选择性信道全矩阵估计方法

更新时间：2026-06-24

- 基于后验加权更新的OFDM/FBMC双选择性信道全矩阵估计方法
- Posterior-Weighted Update-Based Full-Matrix Channel Estimation for Doubly Selective OFDM/FBMC Channels
- 电信科学 2026年
- 作者机构：
  
  重庆邮电大学通信与信息工程学院，重庆 400065
- 作者简介：
  
  杨黎明（1976- ），女，重庆邮电大学通信与信息工程学院高级工程师，主要研究方向为移动通信协议栈软件设计及测试、移动通信空口安全。
  杨坤，1446207898@qq.com
- 基金信息：
  
  重庆市自然科学基金创新发展联合基金（中国星网）(CSTB2023NSCQ-LZX0114)
- DOI：10.11959/j.issn.1000-0801.DXKX260191
  中图分类号： TN929.5
- 收稿：2026-03-24，
  
  修回：2026-05-12，
  
  录用：2026-06-23，
- 稿件说明：
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杨黎明, 杨坤, 陈樑. 基于后验加权更新的OFDM/FBMC双选择性信道全矩阵估计方法[J/OL]. 电信科学, 2026.

YANG Liming, YANG Kun, Chen Liang. Posterior-Weighted Update-Based Full-Matrix Channel Estimation for Doubly Selective OFDM/FBMC Channels[J/OL]. Telecommunications Science, 2026.
杨黎明, 杨坤, 陈樑. 基于后验加权更新的OFDM/FBMC双选择性信道全矩阵估计方法[J/OL]. 电信科学, 2026. DOI： 10.11959/j.issn.1000-0801.DXKX260191.

YANG Liming, YANG Kun, Chen Liang. Posterior-Weighted Update-Based Full-Matrix Channel Estimation for Doubly Selective OFDM/FBMC Channels[J/OL]. Telecommunications Science, 2026. DOI： 10.11959/j.issn.1000-0801.DXKX260191.

摘要

针对双选择性信道条件下OFDM/FBMC系统中传统IR方法容易受到错误数据反馈干扰，导致误差传播并在高信噪比区域出现性能平台的问题，本文提出一种基于后验加权的预测基系数域更新方法。该方法利用当前信道估计得到数据符号的后验均值与后验方差，在预测基系数域内构建加权修正模型，实现全矩阵信道估计的重构。在此基础上，进一步给出了SoftMean和SoftVar两种实现形式。仿真结果表明，所提方法在中高信噪比区间均优于原始IR方法，且优势随信噪比升高更加明显。在35 dB信噪比条件下，所提方法相较原始IR在全矩阵信道估计中的NMSE改善约4 dB，在导频位信道估计中的NMSE改善约2 dB。本文进一步分析了所提方法的计算复杂度，结果表明，新增计算主要来源于后验统计量计算和预测基系数域加权求解。

Abstract

For OFDM/FBMC systems over doubly selective channels

the conventional interference removal (IR) method is susceptible to erroneous data feedback

which leads to error propagation and a performance floor in the high-SNR region. To address this issue

a posterior-weighted prediction-basis coefficient-domain update method is proposed. Based on the current channel estimate

the posterior mean and posterior variance of the data symbols are obtained

and a weighted correction model is constructed in the prediction-basis coefficient domain to reconstruct the full-matrix channel estimate. On this basis

two implementation forms

namely SoftMean and SoftVar

are further developed. Simulation results show that the proposed method outperforms the original IR method in the medium- and high-SNR regions

and that the performance advantage becomes more pronounced as the SNR increases. At an SNR of 35 dB

compared with the original IR method

the proposed method achieves an NMSE improvement of approximately 4 dB for full-matrix channel estimation and approximately 2 dB for pilot-position channel estimation. The computational complexity of the proposed method is also analyzed

and the results indicate that the additional computational cost mainly arises from the calculation of posterior statistics and the weighted solution in the prediction-basis coefficient domain.

关键词

Keywords

references

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