Machine Learning for Robust Beam Tracking in Mobile Millimeter-Wave Systems

Author:

Sarkar Sopan1,Krunz Marwan1,Aykin Irmak1,Manzi David2

Affiliation:

1. University of Arizona,Dept. of Electrical and Computer Engineering,United States

2. Raytheon Corporation,United States

Funder

NSF

Publisher

IEEE

Cited by 4 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. Actively Adaptive Multi-Armed Bandit Based Beam Tracking for mmWave MIMO Systems;2024 IEEE Wireless Communications and Networking Conference (WCNC);2024-04-21

2. Data-Driven Next-Generation Wireless Networking: Embracing AI for Performance and Security;2023 32nd International Conference on Computer Communications and Networks (ICCCN);2023-07

3. Machine Learning for Millimeter Wave and Terahertz Beam Management: A Survey and Open Challenges;IEEE Access;2023

4. Relay Placement for Maximum Flow Rate via Learning and Optimization Over Riemannian Manifolds;IEEE Transactions on Machine Learning in Communications and Networking;2023

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