IRS-assisted millimeter-wave channel estimation based on parallel factorization
A channel estimation algorithm based on parallel factor(PARAFAC)decomposition is pro-posed.Firstly,the channel is modeled according to the inherent sparse characteristics of the mil-limeter-wave channel.Then,the signal matrix is constructed into a three-dimensional tensor by us-ing the characteristics of the block fading channel,and the tensor is decomposed by the parallel factorization algorithm.Then,the compressed sensing(CS)theory is used to transform the decom-posed matrix into a sparse signal recovery problem.Finally,the bilinear alternating least squares(NBALS)algorithm is improved to solve the channel.The simulation shows that compared with the existing BALS algorithm,wBALS algorithm,and LSKRF algorithm,the proposed algorithm improves the estimation accuracy.
国家科技期刊平台
NSTL
万方数据
