Robust Hybrid Beamforming Scheme for Millimeter-Wave Massive-MIMO 5G Wireless Networks
Department of Medical Instrumentation Techniques Engineering, Electrical Engineering Technical College, Middle Technical University, Baghdad 10013, Iraq
Department of Electrical Engineering, College of Electronics and Information Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea
Department of Electrical Engineering, University of Engineering & Technology, Peshawar 814 KPK, Pakistan
Department of Electronics and Communication Engineering, A’Sharqiyah University, Ibra 400, Oman
Author to whom correspondence should be addressed.
Symmetry 2019, 11(11), 1424; https://doi.org/10.3390/sym11111424
Received: 30 September 2019 / Revised: 30 October 2019 / Accepted: 15 November 2019 / Published: 18 November 2019
(This article belongs to the Special Issue Information Technologies and Electronics)
Wireless networks employing millimeter-wave (mmWave) and Massive Multiple-Input Multiple-Output (MIMO) technologies are a key approach to boost network capacity, coverage, and quality of service (QoS) for future communications. They deploy symmetric antennas on a large scale in order to enhance the system throughput and data rate. However, increasing the number of antennas and Radio Frequency (RF) chains results in high computational complexity and more energy requirements. Therefore, to solve these problems, this paper proposes a low-complexity hybrid beamforming scheme for mmWave Massive-MIMO 5G wireless networks. The proposed algorithm is on the basis of alternating the minimum mean square error (Alt-MMSE) hybrid beamforming technique in which the orthogonal properties of the digital matrix were designed, and then the MSE of the transmitted and received signal was reduced. The phase of the analog matrix was obtained from the updated digital matrix. Simulation results showed that the proposed hybrid beamforming algorithm had better performance than existing state-of-the-art algorithms, and similar performance with the optimal digital precoding algorithm.