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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Bibliographic Details
Published in:IEEE access Vol. 8; p. 1
Main Authors: Sim, Min Soo, Lim, Yeon-Geun, Park, Sang Hyun, Dai, Linglong, Chae, Chan-Byoung
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.01.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
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 Access:Get full text
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Summary: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 for initial access, to attain fine beam alignment between a next generation NodeB (gNB) and a user equipment (UE). The current 5G New Radio (NR) standard, however, adopts an exhaustive search-based beam sweeping, which causes time overhead of a half frame for initial beam establishment. In this paper, we propose a deep learning-based beam selection, which is compatible with the 5G NR standard. To select a mmWave beam, we exploit sub-6 GHz channel information. We introduce a deep neural network (DNN) structure and explain how we estimate a power delay profile (PDP) of a sub-6 GHz channel, which is used as an input of the DNN. We then validate its performance with real environment-based 3D ray-tracing simulations and over-the-air experiments with a mmWave prototype. Evaluation results confirm that, with support from the sub-6 GHz connection, the proposed beam selection reduces the beam sweeping overhead by up to 79.3 %.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2980285