Deep Learning-Based mmWave Beam Selection for 5G NR/6G with Sub-6 GHz Channel Information: Algorithms and Prototype Validation

In fifth-generation (5G) communications, millimeter wave (mmWave) is one of the key technologies to increase the data rate. To overcome this technology's poor propagation characteristics, it is necessary to employ a number of antennas and form narrow beams. It becomes crucial then, especially f...

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Veröffentlicht in:	IEEE access Jg. 8; S. 1
Hauptverfasser:	Sim, Min Soo, Lim, Yeon-Geun, Park, Sang Hyun, Dai, Linglong, Chae, Chan-Byoung
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.01.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	5G NR Algorithms and ultra-low latency Artificial neural networks beam selection beamforming Deep learning Machine learning Millimeter waves mmWave Prototypes Ray tracing Sweeping
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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