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PCA-Aided Linear Precoding in Massive MIMO Systems with Imperfect CSI

Dinh, V.-K. and Le, M.-T. and Ngo, V.-D. and Ta, C.-H. (2020) PCA-Aided Linear Precoding in Massive MIMO Systems with Imperfect CSI. Wireless Communications and Mobile Computing, 2020: 3425952. ISSN 15308669

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. © 2020 Van-Khoi Dinh et al.

Item Type: Article
Divisions: Faculties > Faculty of Radio-Electronic Engineering
Identification Number: 10.1155/2020/3425952
Uncontrolled Keywords: Bit error rate; Computational complexity; Mean square error; MIMO systems; Bit error rate (BER) performance; Block diagonalization; Imperfect CSI; Lattice-reduction-aided; Linear pre-coding; Linear precoders; Minimum mean square errors; Two-component; Principal component analysis
Additional Information: Language of original document: English. All Open Access, Gold, Green.
URI: http://eprints.lqdtu.edu.vn/id/eprint/9162

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