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ARTICLE
A Highly Efficient Algorithm for Phased-Array mmWave Massive MIMO Beamforming
1 Department of Electrical Engineering, Jouf University, Sakaka, Aljouf, 72388, Kingdom of Saudi Arabia
2 Department of Computer and Communication Systems Engineering, Faculty of Engineering, Universiti Putra Malaysia (UPM), Serdang, 43400, Malaysia
3 Department of Electrical Engineering, University of Engineering and Technology Peshawar, Pakistan
4 School of Electrical and Electronics Engineering, Chung-Ang University, Seoul, 06974, Korea
5 Electrical and Electronic Department, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
6 UMR 1253, iBrain, Université de Tours, INSERM, Tours, France
7 LIMPAF Laboratory, Department of Computer Science, University of Bouira, Bouira, 10000, Algeria
8 University of Tours (France), GREMAN UMR 7347, CNRS, INSA Centre Val-de-Loire, Tours, 37100, France
* Corresponding Author: Abdeldjalil Ouahabi. Email:
Computers, Materials & Continua 2021, 69(1), 679-694. https://doi.org/10.32604/cmc.2021.015421
Received 20 November 2020; Accepted 30 December 2020; Issue published 04 June 2021
Abstract
With the rapid development of the mobile internet and the internet of things (IoT), the fifth generation (5G) mobile communication system is seeing explosive growth in data traffic. In addition, low-frequency spectrum resources are becoming increasingly scarce and there is now an urgent need to switch to higher frequency bands. Millimeter wave (mmWave) technology has several outstanding features—it is one of the most well-known 5G technologies and has the capacity to fulfil many of the requirements of future wireless networks. Importantly, it has an abundant resource spectrum, which can significantly increase the communication rate of a mobile communication system. As such, it is now considered a key technology for future mobile communications. MmWave communication technology also has a more open network architecture; it can deliver varied services and be applied in many scenarios. By contrast, traditional, all-digital precoding systems have the drawbacks of high computational complexity and higher power consumption. This paper examines the implementation of a new hybrid precoding system that significantly reduces both calculational complexity and energy consumption. The primary idea is to generate several sub-channels with equal gain by dividing the channel by the geometric mean decomposition (GMD). In this process, the objective function of the spectral efficiency is derived, then the basic tracking principle and least square (LS) techniques are deployed to design the proposed hybrid precoding. Simulation results show that the proposed algorithm significantly improves system performance and reduces computational complexity by more than 45% compared to traditional algorithms.Keywords
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