Learning Enhanced Beamforming Vector From CQIs in 5G NR FDD Massive MIMO Systems: A Tuning-free Approach
Author:
Funder
National Natural Science Foundation of China
BD
Research and Development
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9593094/9593095/09593098.pdf?arnumber=9593098
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. CSI Sensing From Heterogeneous User Feedbacks: A Constrained Phase Retrieval Approach;IEEE Transactions on Wireless Communications;2023-10
2. An Exploration-Estimation Beamforming Scheme For 5GNR FDD Massive MIMO Communications;2023 IEEE 24th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC);2023-09-25
3. Downlink CSI Recovery in Massive MIMO Systems by Proactive Sensing;IEEE Wireless Communications Letters;2023-03
4. Machine Learning Codebook Design for Initial Access and CSI Type-II Feedback in Sub-6GHz 5G NR;IEEE Transactions on Wireless Communications;2023
5. Sparsity-Structured Tensor-Aided Channel Estimation for RIS-Assisted MIMO Communications;IEEE Communications Letters;2022-10
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