Calculating Beamforming Vectors for 5G System Applications

Author:

Dmitriyev EdgarORCID,Rogozhnikov Eugeniy,Duplishcheva Natalia,Novichkov Serafim

Abstract

The growing demand for broadband Internet services is forcing scientists around the world to seek and develop new telecommunication technologies. With the transition from the fourth generation to the fifth generation wireless communication systems, one of these technologies is beamforming. The need for this technology was caused by the use of millimeter waves in data transmission. This frequency range is characterized by heavy path loss. The beamforming technology could compensate for this significant drawback. This paper discusses basic beamforming schemes and proposes a model implemented on the basis of QuaDRiGa. The model implements a MIMO channel using symmetrical antenna arrays. In addition, the methods for calculating the antenna weight coefficients based on the channel matrix are compared. The first well-known method is based on the addition of cluster responses to calculate the coefficients. The proposed one uses the singular value decomposition of the channel matrix into clusters to take into account the most correlated information between all clusters when calculating the antenna coefficients. According to the research results, the proposed method for calculating the antenna coefficients allows an increase in the SNR/SINR level by 8–10 dB on the receiving side in the case of analog beamforming with a known channel matrix.

Funder

Russian Venture Company

Skolkovo Institute of Science and Technology

Publisher

MDPI AG

Subject

Physics and Astronomy (miscellaneous),General Mathematics,Chemistry (miscellaneous),Computer Science (miscellaneous)

Reference17 articles.

1. List of 5G NR Networkshttps://en.wikipedia.org/wiki/List_of_5G_NR_networks

2. QuaDRiGa: A 3-D Multi-Cell Channel Model With Time Evolution for Enabling Virtual Field Trials

3. A Geometric Polarization Rotation Model for the 3-D Spatial Channel Model

4. QuaDRiGahttps://quadriga-channel-model.de

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Mitigating Security Risks in 6G Networks-Based Optimization of Deep Learning;GLOBECOM 2023 - 2023 IEEE Global Communications Conference;2023-12-04

2. Intelligent Beamforming Design in mmWave mMIMO: A Reinforcement Learning Approach;2022 13th International Conference on Information and Communication Technology Convergence (ICTC);2022-10-19

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