北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2017, Vol. 40 ›› Issue (3): 62-66.doi: 10.13190/j.jbupt.2017.03.008

• 论文 • 上一篇    下一篇

OFDM系统中基于降维PARAFAC模型的信道估计方法

林和昀1, 袁超伟1, 杜建和2   

  1. 1. 北京邮电大学 信息与通信工程学院, 北京 100876;
    2. 中国传媒大学 信息工程学院, 北京 100024
  • 收稿日期:2017-01-12 出版日期:2017-06-28 发布日期:2017-05-25
  • 作者简介:林和昀(1985-),男,博士生;袁超伟(1960-),男,教授,博士生导师,E-mail:yuancw2000@bupt.edu.cn.
  • 基金资助:
    国家高技术研究发展计划(863计划)项目(2015AA01A705,2014AA01A701);国家自然科学基金项目(61601414)

Channel Estimation for OFDM Systems Via Reduced-Dimensional PARAFAC Method

LIN He-yun1, YUAN Chao-wei1, DU Jian-he2   

  1. 1. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China;
    2. School of Information and Engineering, Communication University of China, Beijing 100024, China
  • Received:2017-01-12 Online:2017-06-28 Published:2017-05-25

摘要: 针对采用正交频分复用(OFDM)技术的阵列天线系统,提出了一种基于降维平行因子(PARAFAC)模型的多径信道估计方法.该方案对单输入多输出(SIMO)场景下的接收信号进行建模,构造出具有空-时-频3个维度的PARAFAC信号模型,利用截尾奇异值分解(SVD)法对该模型进行降维,并采用三线性交替最小二乘(TALS)算法对降维后的信号模型进行拟合,实现了信号到达角(AOA)和传播时延的联合估计.与传统PARAFAC分解方法相比,所提方法在拟合过程中占用的存储空间更少,收敛速度更快.仿真结果验证了所提方法的有效性.

关键词: 多维矩阵, 平行因子模型, 正交频分复用, 联合估计

Abstract: The article presents a joint angle and propagation delay estimation approach in an orthogonal frequency division multiplexing (OFDM) system via reduced-dimension parallel factor (PARAFAC) method. Firstly, the received signal was formulated as a three-order PARAFAC model in a single input multiple output (SIMO) OFDM system. Truncated singular value decomposition (SVD) was exploited to reduce the dimension of the PARAFAC model. Then a trilinear alternating least square (TALS)algorithm based on the reduced dimensional PARAFAC model was presented to jointly recover the angle-of-arrival (AOA) and propagation delay. Compared with the conventional parallel factor decomposition method, the approach has much smaller memory capacity and lower computation complexity. Simulations validate the effectiveness of our method.

Key words: multi-way, parallel factor model, orthogonal frequency division multiplexing, jointly estimate

中图分类号: