采用数据辅助的大规模MIMO信道半盲迭代估计

由于大规模多输入多输出(Multiple-Input Multiple-Output,MIMO)信道衰落参数的维度较高,导致最优估计算法计算量大且需要的导频数较多而影响到频谱效率.为降低计算复杂度并减少导频开销,提出了两种基于期望最大化(Expectation Maximization,EM)估计的半盲迭代改进算法.利...

Semi-blind Iterative Estimation of Massive MIMO Channel with Data Assistance

Due to the high dimension of the fading parameters for massive multiple-input multiple-output(MIMO) channel,the computation burden of optimal estimation algorithms is heavy along with the large number of pilots which affects spectral efficiency.To reduce the computational complexity and pilot overhead,two improved semi-blind iterative algorithms based on expectation maximization(EM) estimation are proposed.A small number of orthogonal pilot sequences are used to estimate the initial values.Users are clustered into several groups by exploiting the large-scale fading coefficients between users and base station.Thus,the received noise is proportionally assigned according to these coefficients.The mean and variance of channel parameters are then derived using the statistical characteristics of data.Simulation results show that the mean square error(MSE) of the algorithm is better than that of the maximum likelihood(ML) algorithm when the number of pilots is far less than the estimated parameters.