针对可重构智能表面(Reconfigurable Intelligent Surface,RIS)辅助波束空间多输入多输出(Multiple Input Multiple Output,MIMO)系统信道状态信息获取难度大的问题,提出了一种基于张量的迭代信道估计算法.构建了基站接收导频信号的三阶张量模型,模型的3个维度包括基站天线数、用户数以及RIS相位配置数;采用并行因子(Parallel Factor,PARAFAC)分解和交替最小二乘(Alternative Least Squares,ALS)算法对该系统中的信道进行估计并得到了闭式解,理论分析了所提算法的可行性条件;在仿真实验中讨论了不同系统参数对信道估计性能的影响.仿真实验结果表明,该算法利用PARAFAC特定代数结构获得了良好的信道估计性能.
Tensor-based Channel Estimation for RIS Assisted Beam-space MIMO Systems
A tensor-based iterative channel estimation algorithm is proposed to address the difficulty in obtaining channel state information for Reconfigurable Intelligent Surface(RIS)assisted beam-space Multiple Input Multiple Output(MIMO)systems.A third-order tensor model is constructed for the received pilot signal at the base station and the three dimensions of the model include the number of antennas at the base station,the number of users and the number of RIS phase configurations;Parallel Factor(PARAFAC)decomposition and Alternating Least Squares(ALS)algorithms are used to estimate the channels in this system and closed form solutions are obtained,the feasibility conditions of the proposed algorithm is theoretically analyzed;the impacts of different system parameters on channel estimation performance are also discussed in the simulation experiments.Simulation experimental results show that the proposed algorithm using the PARAFAC-specific algebraic structure obtains good channel estimation performance.
万方数据
维普
