OFDM系统中基于降维PARAFAC模型的信道估计方法

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.

Channel Estimation for OFDM Systems Via Reduced-Dimensional PARAFAC Method

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.