Deep Scanning-Beam Selection Based on Deep Reinforcement Learning in Massive MIMO Wireless Communication System

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In this paper, we investigate a deep learning based resource allocation scheme for massive multiple-input-multiple-output (MIMO) communication systems, where a base station (BS) with a large scale antenna array communicates with a user equipment (UE) using beamforming. In particular, we propose Deep Scanning, in which a near-optimal beamforming vector can be found based on deep Q-learning. Through simulations, we confirm that the optimal beam vector can be found with a high probability. We also show that the complexity required to find the optimum beam vector can be reduced significantly in comparison with conventional beam search schemes.
Publisher
MDPI
Issue Date
2020-11
Language
English
Article Type
Article
Citation

ELECTRONICS, v.9, no.11

ISSN
2079-9292
DOI
10.3390/electronics9111844
URI
http://hdl.handle.net/10203/279303
Appears in Collection
EE-Journal Papers(저널논문)
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