基于张量分解的MIMO多中继系统半盲信道估计方法  

Tensor-Based Semi-Blind Channel Estimation Method for Three-Hop MIMO Relay Systems

作　　者：穆晓敏[1] 刘越[1] 李双志[1] 张建康[1] MU Xiaomin LIU Yue LI Shuangzhi ZHANG Jiankang(School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China)

机构地区：[1]郑州大学信息工程学院,河南郑州450001

出　　处：《郑州大学学报（工学版）》2016年第6期83-86,96,共5页Journal of Zhengzhou University（Engineering Science）

基　　金：国家自然科学基金资助项目(61271421);国家自然科学基金青年科学基金资助项目(61301150)

摘　　要：针对多输入多输出三跳中继系统,提出了一种基于张量分解的半盲信道估计方法.该方法通过对接收信号构造基于张量分解的PARAFAC和PARATUCK2模型,通过两阶段的迭代算法拟合张量模型.两阶段迭代算法利用ALS拟合PARAFAC模型估计复合信道和发送信号,并利用TALS拟合PARATUCK2模型并行估计三跳信道矩阵.与已有的信道估计方法相比,该方法只需少量的导频序列便能并行估计三跳信道矩阵,不仅可以避免误差叠加,而且提高了系统的频谱利用率,仿真结果验证了其有效性.A novel semi-blind channel estimation was devised to jointly estimate the channel matrices of all links in a three-hop multiple-input multiple-output relay system. A PARAFAC and a PARATUCK2 tensor model of the received signal were constructed, and the proposed algorithm used a two-stage iterative fitting al- gorithm for tensor model. The ALS algorithm was used to fit the PARAFAC tensor model in the process of esti- mating the compound channel matrix. Then the TALS algorithm was used to fit the PARATUCK2 tensor model in the process of extracting all the sub-channel matrices. The proposed algorithm could loose the limitation on the number of antennas at the destination node. Moreover, compared with existing methods, the proposed al- gorithm could avoid error propagation as well as improve the spectral efficiency with few pilots. Numerical ex- amples demonstrated the effectiveness of the proposed algorithm.

关 键 词：MIMO多中继系统 半盲信道估计 张量分解 两阶段迭代算法 

分 类 号：TN92[电子电信—通信与信息系统]