Next Article in Journal
Quantum Analogs of Ostrowski-Type Inequalities for Raina’s Function correlated with Coordinated Generalized Φ-Convex Functions
Next Article in Special Issue
Compact Square-Wave Pulse Electroporator with Controlled Electroporation Efficiency and Cell Viability
Previous Article in Journal
Decision to Adopt Neuromarketing Techniques for Sustainable Product Marketing: A Fuzzy Decision-Making Approach
Previous Article in Special Issue
A Privacy Preserving Authentication Scheme for Roaming in IoT-Based Wireless Mobile Networks
Open AccessArticle

A Robust Hybrid Iterative Linear Detector for Massive MIMO Uplink Systems

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(2), 306; https://doi.org/10.3390/sym12020306
Received: 23 January 2020 / Revised: 9 February 2020 / Accepted: 17 February 2020 / Published: 21 February 2020
(This article belongs to the Special Issue Information Technologies and Electronics)
Fifth-generation (5G) communications system is commercially introduced by several mobile operators where sub-6 GHz bands are the backbone of the 5G networks. A large-scale multiple-input multiple-output (MIMO), or massive MIMO (mMIMO), technology has a major impact to secure high data rate, high spectral efficiency, and quality of service (QoS). It could also have a major role in the beyond-5G systems. A massive number of antennas seek advanced signal processing to detect and equalize the signal. However, optimal detectors, such as the maximum likelihood (ML) and maximum posterior (MAP), are not desirable in implementation due to extremely high complexity. Therefore, sub-optimum solutions have been introduced to obtain and guarantee enough balance between the performance and the computational complexity. In this paper, a robust and joint low complexity detection algorithm is proposed based on the Jacobi (JA) and Gauss–Seidel (GS) methods. In such iterative methods, the performance, complexity, and convergence rate are highly dependent on the initial vector. In this paper, initial solution is proposed by exploiting the benefits of a stair matrix to obtain a fast convergence rate, high performance, and low complexity. Numerical results show that proposed algorithm achieves high accuracy and relieve the computational complexity even when the BS-to-user-antenna ratio (BUAR) is small. View Full-Text
Keywords: 5G; Massive MIMO; iterative methods; stair matrix; Neumann series; successive overrelaxation; Gauss–Seidel; Jacobi 5G; Massive MIMO; iterative methods; stair matrix; Neumann series; successive overrelaxation; Gauss–Seidel; Jacobi
Show Figures

Graphical abstract

MDPI and ACS Style

Albreem, M.A.; Alsharif, M.H.; Kim, S. A Robust Hybrid Iterative Linear Detector for Massive MIMO Uplink Systems. Symmetry 2020, 12, 306. https://doi.org/10.3390/sym12020306

AMA Style

Albreem MA, Alsharif MH, Kim S. A Robust Hybrid Iterative Linear Detector for Massive MIMO Uplink Systems. Symmetry. 2020; 12(2):306. https://doi.org/10.3390/sym12020306

Chicago/Turabian Style

Albreem, Mahmoud A.; Alsharif, Mohammed H.; Kim, Sunghwan. 2020. "A Robust Hybrid Iterative Linear Detector for Massive MIMO Uplink Systems" Symmetry 12, no. 2: 306. https://doi.org/10.3390/sym12020306

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop