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.

Highlights

  • As the number of wireless devices continues to grow and wireless applications continue to expand, user demand for wireless network transmission rates continues to increase

  • This section analyses the performance of the geometric mean decomposition (GMD)-based hybrid precoding scheme and spatial sparse precoding through simulation

  • For all sub-channels based on singular value decomposition (SVD) and GMD precoding schemes, the 16QAM modulation method is adopted

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Summary

A Highly Efficient Algorithm for Phased-Array mmWave Massive MIMO Beamforming

CMC-Computers, Materials & Continua, Tech Science Press, 2021, 69 (1), pp.679694. HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Ayman Abdulhadi Althuwayb, Fazirulhisyam Hashim, Jiun Terng Liew, Imran Khan Jeong Woo Lee, Emmanuel Ampoma Affum, Abdeldjalil Ouahabi6,7,* and Sébastien Jacques

Introduction
Hybrid Precoding Model
Channel Model
Problem Description
Optimization of Spectral Efficiency
Conversion Optimization Objective Function
Optimize Objective Function Solution
Optimization Algorithm Under Fully Connected Structure
Optimization Algorithm Under Partially Connected Structure
Simulation Results
Conclusions

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