Deep scanning - Beam selection based on deep reinforcement learning in massive MIMO wireless communication system

Kim, Minhoe; Lee, Woongsup; Cho, Dong-Ho
Electronics, November 2020, 9(11), 1844

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.


DOI
Type:
Journal
Date:
2020-11-03
Department:
Systèmes de Communication
Eurecom Ref:
6399
Copyright:
MDPI
See also:

PERMALINK : https://www.eurecom.fr/publication/6399