University of Oulu

M. A. M. Albreem, A. A. El-Saleh and M. Juntti, "On Approximate Matrix Inversion Methods for Massive MIMO Detectors," 2019 IEEE Wireless Communications and Networking Conference (WCNC), Marrakesh, Morocco, 2019, pp. 1-6, doi: 10.1109/WCNC.2019.8885673

On approximate matrix inversion methods for massive MIMO detectors

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Author: Albreem, Mahmoud A. M.1; El-Saleh, Ayman A.1; Juntti, Markku2
Organizations: 1A’Sharqiyah University Ibra, Oman
2University of Oulu Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.4 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2019
Publish Date: 2020-05-12


Massive multiple-input multiple-output (MIMO) systems have been proposed to meet the user demands in terms of performance and quality of service (QoS). Due to the large number of antennas, detectors in massive MIMO are playing a crucial role in guaranteeing a satisfactory performance, while their complexity is also being increased. This paper considers several approximate algorithms to avoid direct matrix inversion, namely the Neumann method, the Gauss-Seidel (GS) method, the successive over-relaxation (SOR) method, the Jacobi method, the Richardson method, the optimized coordinate descent (OCD), and the conjugate gradients (CG) method. Also, this paper presents a comparison among the approximate matrix inversion methods and the minimum mean square error (MMSE). Simulation of 16×128, and 16×32 MIMO systems shows that a detector based on the GS method outperforms other detectors when the ratio of base station (BS) antennas to user terminal antennas, β, is small. On the other hand, the detector based on the SOR method outperforms the other approximate matrix inversion methods when β is large. In addition, this paper studies and recommends the setting values of relaxation parameter (ω) in the SOR and Richardson methods. It also provides a comparison among the approximate matrix inversion methods in the number of multiplications. Simulation results show that the Neumann method, the OCD method, and the CG method achieve the lowest number of multiplications while the CG method outperforms the Neumann and the OCD methods. This paper also shows that not every iteration improves the performance.

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Series: IEEE Wireless Communications and Networking Conference
ISSN: 1525-3511
ISSN-E: 1558-2612
ISSN-L: 1525-3511
ISBN: 978-1-5386-7646-2
ISBN Print: 978-1-5386-7647-9
Pages: 1 - 6
DOI: 10.1109/WCNC.2019.8885673
Host publication: 2019 IEEE Wireless Communications and Networking Conference (WCNC), 15-18 April 2019, Marrakesh, Morocco
Conference: IEEE Wireless Communications and Networking Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: Authors would like to thank A’Sharqiyah University (ASU) for the conference travel grant.
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