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- Title
基于深度学习的毫米波系统波束成形.
- Authors
龙恳; 王亚领; 陈兴; 王奕; 谭路垚
- Abstract
A novel integrated deep learning coordinated beamforming(DLCBF) solution is proposed to address the problem of frequent switching between users and base stations in millimeter wave systems with high mobile users, which increases the latency overhead. By coordinating multiple base stations to serve a mobile user and receiving the user uplink conduction sequences and pre-coded codebook training model, the DLCBF solution can predict the optimal downlink beamforming vector, thus overcoming the large training overhead required to select the optimal beamforming vector for large antenna array millimeter wave systems. Simulation results show that the proposed solution is more spectrally efficient than conventional millimeter wave beamforming strategies.
- Subjects
MILLIMETER wave antennas; MILLIMETER waves; DEEP learning; BEAMFORMING; MIMO systems
- Publication
Telecommunication Engineering, 2021, Vol 61, Issue 2, p131
- ISSN
1001-893X
- Publication type
Article
- DOI
10.3969/j.issn.1001-893x.2021.02.001