张伟涛,
楼顺天
西安电子科技大学电子工程学院 ??西安 ??710071
基金项目:国家自然科学基金(61571339)，陕西省创新人才推进计划-青年科技新星项目(2018KJXX-019)
详细信息
作者简介:杨若男：女，1993年生，博士生，研究方向为MIMO-OFDM系统盲信道估计
张伟涛：男，1983年生，副教授，硕士生导师，研究方向为盲信号处理、语音信号处理等
楼顺天：男，1962年生，教授，博士生导师，研究方向为神经网络信息处理与应用、模糊信息处理与应用、盲信号处理、现代信号智能处理、智能控制技术等
通讯作者:杨若男 rn_yang@163.com
中图分类号:TN911.7计量
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被引次数:0
出版历程
收稿日期:2018-05-07
修回日期:2018-10-25
网络出版日期:2018-11-19
刊出日期:2019-03-01
Joint Blind Channel Estimation and Symbols Detection for SIMO-OFDM Systems Based on PARAFAC
Ruonan YANG,,Weitao ZHANG,
Shuntian LOU
School of Electronic Engineering, Xidian University, Xi’an 710071, China
Funds:The National Natural Science Foundation of China (61571339), The Natural Science Foundation of Shaanxi Province (2018KJXX-019)
摘要
摘要:针对SIMO-OFDM系统下的信道估计和符号检测问题，该文建立了接收数据矩阵的平行因子分析(PARAFAC)模型，利用PARAFAC模型中离散傅里叶变换矩阵的行满秩特性，结合数据矩阵的奇异值分解，提出了一种信道与符号联合盲估计的闭式求解方法。由于提出的求解方法无须进行迭代便可以完成信道估计和符号检测，因此其计算复杂度低，此外，利用PARAFAC模型实现信道和符号的同时计算，避免了因信道估计误差导致的符号误码率性能下降问题。仿真结果表明，与传统方法相比提出的方法计算复杂度更低，估计性能更好。
关键词:盲信道估计/
符号检测/
SIMO-OFDM/
平行因子分析
Abstract:To solve the problem of the joint blind channel estimation and symbol detection for SIMO-OFDM systems, a PARAllel FACtor (PARAFAC) analysis model of the receive data matrix is established. Then, with the full row rank characteristic of the discrete Fourier transform matrix and the singular value decomposition of the receiving data matrix, a closed method is proposed for joint blind channel estimation and symbol detection. The proposed method has low computational complexity because it has no iteration. Furthermore, by the simultaneously calculated of channel and signals, the proposed method can avoid the performance reduction of signal estimation caused by channel estimation error. Simulation results show that the proposed method has lower computational complexity and better estimation performance compared with traditional methods.
Key words:Blind channel estimation/
Symbols detection/
SIMO-OFDM/
PARAllel FACtor (PARAFAC) analysis
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