RSSI-Based Hybrid Beamforming Design with Deep Learning
Author:
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9141367/9148588/09149321.pdf?arnumber=9149321
Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Learning Energy-Efficient Transmitter Configurations for Massive MIMO Beamforming;IEEE Transactions on Machine Learning in Communications and Networking;2024
2. Spatial attention and quantization-based contrastive learning framework for mmWave massive MIMO beam training;EURASIP Journal on Wireless Communications and Networking;2023-07-25
3. Switching Strategy for Connected Vehicles Under Variant Harsh Weather Conditions;IEEE Journal of Radio Frequency Identification;2023
4. Flexible Unsupervised Learning for Massive MIMO Subarray Hybrid Beamforming;GLOBECOM 2022 - 2022 IEEE Global Communications Conference;2022-12-04
5. Decentralized Beamforming for Cell-Free Massive MIMO With Unsupervised Learning;IEEE Communications Letters;2022-05
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