3d beamforming
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2021 ◽  
Author(s):  
Shraddha Tripathi ◽  
Om Jee Pandey ◽  
Rajesh M. Hegde


Author(s):  
钰达 林 ◽  
梁 金 ◽  
开枝 黄 ◽  
乾 韩


Author(s):  
Sinan A. Khwandah ◽  
John P. Cosmas ◽  
Pavlos I. Lazaridis ◽  
Zaharias D. Zaharis ◽  
Ioannis P. Chochliouros

AbstractMassive MIMO will improve the performance of future 5G systems in terms of data rate and spectral efficiency, while accommodating a large number of users. Furthermore, it allows for 3D beamforming in order to provide more degrees of freedom and increase the number of high-throughput users. Massive MIMO is expected to provide more advantages compared to other solutions in terms of energy and spectral efficiency. This will be achieved by focusing the radiation towards the direction of the intended users, thus implementing simultaneous transmission to many users while keeping interference low. It can boost the capacity compared to a conventional antenna solution, resulting in a spectral efficiency up to 50 times greater than that provided by actual 4G technology. However, to take full advantage of this technology and to overcome the challenges of implementation in a real environment, a complicated radio system is required. The purpose of this work is to present the MIMO technology evolution and challenges in a simple introductory way and investigate potential system enhancements.



2021 ◽  
Vol 11 (4) ◽  
pp. 1751
Author(s):  
Marta Bonato ◽  
Laura Dossi ◽  
Emma Chiaramello ◽  
Serena Fiocchi ◽  
Gabriella Tognola ◽  
...  

The deployment of near future 5G networks will introduce modifications in the population’s exposure levels to radio-frequency electromagnetic fields (RF-EMFs). The present work aimed to face the challenge of studying the exposure variability in the presence of an access point (AP) at 3.7 GHz with 64 patch elements uniform planar array antenna and 3D beamforming capability. The novelty introduced in the methodology of the exposure’s evaluation was the combining of traditional computational methods with a new approach based on stochastic dosimetry, called polynomial chaos kriging method, in order to estimate the exposure levels for 1000 different antenna beamforming patterns with low computational efforts. The simulations were evaluated considering a child model and computing the specific absorption rate (SAR) in different tissues. The analysis of the results highlighted a high exposure variability scenario depending on the beamforming patterns of the array antenna and identified the ranges of elevation and azimuth angles of the main antenna beam that may cause the highest levels of exposure.



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