Malar, E (2022) Hybrid Beamforming in Large-scale Antenna Array for 5G Indoor Communication Network Deployments. Wireless Personal Communications, 126 (3). pp. 2513-2532. ISSN 0929-6212
Full text not available from this repository.Abstract
The millimeter-wave multiple input multiple output (MIMO) technology is the frontier for 5G communication systems. This work contributes a large antenna array with a limited number of radio frequency chains using the hybrid beamforming (HBF) technique that overcomes extreme path loss in the mmWave system to improve spectral efficiency. The link budget analysis is given for the target data rate of 11.3 Gbps for the point-to-point communication. The number of antenna elements required for the proposed antenna array is determined via link budget analysis. The proposed link budget is verified using the New York University Simulator (NYUSIM) to perform large scale and small scale fading, power spectrum and omnidirectional and directional power delay profile analysis with given specific network parameters. Combiners and hybrid precoders are designed together in an iterative way for reducing the cost function of the weighted minimum mean squared(WMMSE) error. Simulation results demonstrate that the proposed HBF algorithm performance is highly effective and performs closer to the fully digital beamforming technique. The proposed large antenna array with HBF methodology provides an optimal approach to indoor point-to-point communication deployments.
Item Type: | Article |
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Uncontrolled Keywords: | Beam forming networks; Beamforming; Budget control; Cost functions; Fading (radio); Fading channels; Iterative methods; Millimeter waves; MIMO systems; Omnidirectional antennas; Spectrum efficiency, 5g point-to-point communication; Beamforming technique; Hybrid beamforming; Indoor communications; Large antennas; Large-scales; Link budget analysis; Link budgets; Mm waves; Point-to-point communication, 5G mobile communication systems |
Subjects: | E Electronics and Communication Engineering > Antennas |
Divisions: | Electrical and Electronics Engineering |
Depositing User: | Users 5 not found. |
Date Deposited: | 13 May 2024 09:14 |
Last Modified: | 13 May 2024 09:14 |
URI: | https://ir.psgitech.ac.in/id/eprint/553 |