基于共轭梯度法的低复杂度信道估计

考虑在大规模MIMO系统中基于导频的信道估计,基站端配置有数百根天线,传统的MMSE估计器虽然在估计精度上有着良好的性能,但是由于在利用MMSE方法进行信道估计时,存在对协方差矩阵求逆的运算,导致其计算复杂度为OM3,其中M为信道协方差矩阵的维度。在基站天线数很大的时候,这将是一个极其复杂的过程。为解决这个问题,将通过将求逆过程转化为解线性方程组的问题,利用共轭梯度法,使整个计算过程的计算复杂度降为ONM2,其中N为共轭梯度法的迭代次数,而且N<

Low-Complexity Channel Estimation based on Conjugate Gradient

In consideration of pilot-based channel estimation in large-scale MIMO (Multiple-Input Multiple-Output) communication systems,hundreds of antennas are equipped at the base station. Conventional MMSE estimator enjoys good performance in the estimation accuracy, and however, when MMSE channel estimation method is used to implement estimation,the operation of covariance matrix inversion would result in computational complexity of O(M3),M meaning the dimension of channel covariance matrix,and when the base station is equipped with hundreds of antennas, this would be an extremely complex process. To solve this problem, the inversion process is transformed into solution of linear equations, thus the computation complexity of the whole process is reduced to O(NM2) through conjugate gradient method, N meaning the iterations number of conjugate gradient algorithm and N<