OFDM系统中基于降维PARAFAC模型的信道估计方法  

Channel Estimation for OFDM Systems Via Reduced-Dimensional PARAFAC Method

作　　者：林和昀[1] 袁超伟[1] 杜建和[2] LIN He-yun YUAN Chao-wei DU Jian-he(School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China School of Information and Engineering, Communication University of China, Beijing 100024, China)

机构地区：[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

出　　处：《北京邮电大学学报》2017年第3期62-66,共5页Journal of Beijing University of Posts and Telecommunications

基　　金：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);国家电网总部科技项目"超高海拔超高压长链式电网输变电关键技术研究与设备研制"

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.The article presents a joint angle and propagation delay estimation approach in an orthogonal frequency division multiplexing （OFDM） system via reduced-dimensional 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.

关 键 词：多维矩阵 平行因子模型 正交频分复用 联合估计 

分 类 号：TN911.22[电子电信—通信与信息系统]