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- Title
PCA-Aided Linear Precoding in Massive MIMO Systems with Imperfect CSI.
- Authors
Dinh, Van-Khoi; Le, Minh-Tuan; Ngo, Vu-Duc; Ta, Chi-Hieu
- Abstract
In this paper, a low-complexity linear precoding algorithm based on the principal component analysis technique in combination with the conventional linear precoders, called Principal Component Analysis Linear Precoder (PCA-LP), is proposed for massive MIMO systems. The proposed precoder consists of two components: the first one minimizes the interferences among neighboring users and the second one improves the system performance by utilizing the Principal Component Analysis (PCA) technique. Numerical and simulation results show that the proposed precoder has remarkably lower computational complexity than its low-complexity lattice reduction-aided regularized block diagonalization using zero forcing precoding (LC-RBD-LR-ZF) and lower computational complexity than the PCA-aided Minimum Mean Square Error combination with Block Diagonalization (PCA-MMSE-BD) counterparts while its bit error rate (BER) performance is comparable to those of the LC-RBD-LR-ZF and PCA-MMSE-BD ones.
- Subjects
MIMO systems; PRINCIPAL components analysis; CODING theory; VIDEO coding; COMPUTATIONAL complexity; LINEAR statistical models; ERROR rates
- Publication
Wireless Communications & Mobile Computing, 2020, p1
- ISSN
1530-8669
- Publication type
Article
- DOI
10.1155/2020/3425952