Subspace-Based Semi-Blind Channel Estimation for Large-Scale Multi-Cell Multiuser MIMO Systems

A Joint Approach for Low-Complexity Channel Estimation in 5G Massive MIMO Systems

“…In order to overcome the shortcomings of the above algorithms, especially [13], we proposed an improved joint SVD and ILSP algorithm to effectively improve the detection performance and reduce the computational complexity of the channel estimation in massive MIMO system. Moreover, the proposed scheme will be compared with the existing techniques to provide a clear indication of the relative advantages of the proposed algorithm over the existing algorithms.…”

“…The precondition is that each channel vector is approximately orthogonal, but the actual situation is that the channel vector is not completely orthogonal, so there is a certain deviation in the method. In [13], a semi-blind channel estimation algorithm based on Singular Value Decomposition (SVD) is proposed for massive MIMO system. Compared to the EVD estimation performance, the performance of the SVD algorithm is significantly improved.…”

“…In order to improve the accuracy of channel estimation in a massive MIMO system, an improved semi-blind channel estimation algorithm based on SVD (SVD-ILSP) is proposed to overcome the shortcomings in [13]. As the existing SVD algorithm in [13] is based on the assumption that the covariance matrix is obtained by using limited sample data instead of real data.…”

“…In order to improve the accuracy of channel estimation in a massive MIMO system, an improved semi-blind channel estimation algorithm based on SVD (SVD-ILSP) is proposed to overcome the shortcomings in [13]. As the existing SVD algorithm in [13] is based on the assumption that the covariance matrix is obtained by using limited sample data instead of real data. This assumption limits the performance of [13] which motivates the proposed research work in which the novel contribution is to overcome the limitations of [13] and propose an improved SVD-ILSP algorithm to efficiently estimate the channel with high accuracy than [13].…”

“…As the existing SVD algorithm in [13] is based on the assumption that the covariance matrix is obtained by using limited sample data instead of real data. This assumption limits the performance of [13] which motivates the proposed research work in which the novel contribution is to overcome the limitations of [13] and propose an improved SVD-ILSP algorithm to efficiently estimate the channel with high accuracy than [13]. The performance of channel estimation is compared with existing algorithms [12,13] by simulation.…”