Deep Learning Based Decentralized Beamforming Methods for Multi-Antenna Interference Channels
This paper develops deep learning (DL) based beamforming approaches for multi-antenna interference channels where several base stations (BSs) individually optimize their own beamforming vectors in a decentralized manner. By exploiting the optimal beam structure, we propose an efficient method for be...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10347192/ |