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Open AccessArticle

Impact of Stair and Diagonal Matrices in Iterative Linear Massive MIMO Uplink Detectors for 5G Wireless Networks

1
Department of Electronics and Communications Engineering, A’Sharqiyah University, Ibra 400, Oman
2
Department of Electrical Engineering, College of Electronics and Information Engineering, Sejong University, 209 Neugdong-ro, Gwangjin-gu, Seoul 05006, Korea
3
School of Electrical Engineering, University of Ulsan, Ulsan 44610, Korea
*
Author to whom correspondence should be addressed.
Symmetry 2020, 12(1), 71; https://doi.org/10.3390/sym12010071
Received: 23 November 2019 / Revised: 22 December 2019 / Accepted: 28 December 2019 / Published: 2 January 2020
(This article belongs to the Special Issue Information Technologies and Electronics)
In massive multiple-input multiple-output (M-MIMO) systems, a detector based on maximum likelihood (ML) algorithm attains optimum performance, but it exhaustively searches all possible solutions, hence, it has a very high complexity and realization is denied. Linear detectors are an alternative solution because of low complexity and simplicity in implementation. Unfortunately, they culminate in a matrix inversion that increases the computational complexity in high loaded systems. Therefore, several iterative methods have been proposed to approximate or avoid the matrix inversion, such as the Neuamnn series (NS), Newton iterations (NI), successive overrelaxation (SOR), Gauss–Siedel (GS), Jacobi (JA), and Richardson (RI) methods. However, a detector based on iterative methods requires a pre-processing and initialization where good initialization impresses the convergence, the performance, and the complexity. Most of the existing iterative linear detectors are using a diagonal matrix ( D ) in initialization because the equalization matrix is almost diagonal. This paper studies the impact of utilizing a stair matrix ( S ) instead of D in initializing the linear M-MIMO uplink (UL) detector. A comparison between iterative linear M-MIMO UL detectors with D and S is presented in performance and computational complexity. Numerical Results show that utilization of S achieves the target performance within few iterations, and, hence, the computational complexity is reduced. A detector based on the GS and S achieved a satisfactory bit-error-rate (BER) with the lowest complexity. View Full-Text
Keywords: Massive MIMO; Neumann series; Newton iteration; successive overrelaxation; Gauss–Seidel; Jacobi; Richardson; diagonal matrix; stair matrix Massive MIMO; Neumann series; Newton iteration; successive overrelaxation; Gauss–Seidel; Jacobi; Richardson; diagonal matrix; stair matrix
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MDPI and ACS Style

Albreem, M.A.; Alsharif, M.H.; Kim, S. Impact of Stair and Diagonal Matrices in Iterative Linear Massive MIMO Uplink Detectors for 5G Wireless Networks. Symmetry 2020, 12, 71. https://doi.org/10.3390/sym12010071

AMA Style

Albreem MA, Alsharif MH, Kim S. Impact of Stair and Diagonal Matrices in Iterative Linear Massive MIMO Uplink Detectors for 5G Wireless Networks. Symmetry. 2020; 12(1):71. https://doi.org/10.3390/sym12010071

Chicago/Turabian Style

Albreem, Mahmoud A.; Alsharif, Mohammed H.; Kim, Sunghwan. 2020. "Impact of Stair and Diagonal Matrices in Iterative Linear Massive MIMO Uplink Detectors for 5G Wireless Networks" Symmetry 12, no. 1: 71. https://doi.org/10.3390/sym12010071

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