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A Tutorial on Beam Management for 3GPP NR at mmWave Frequencies

arXiv 1804.01908 ↗First posted 5 Apr 2018cs.NIcited by 33

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Abstract (arXiv)

The millimeter wave (mmWave) frequencies offer the availability of huge bandwidths to provide unprecedented data rates to next-generation cellular mobile terminals. However, mmWave links are highly susceptible to rapid channel variations and suffer from severe free-space pathloss and atmospheric absorption. To address these challenges, the base stations and the mobile terminals will use highly directional antennas to achieve sufficient link budget in wide area networks. The consequence is the need for precise alignment of the transmitter and the receiver beams, an operation which may increase the latency of establishing a link, and has important implications for control layer procedures, such as initial access, handover and beam tracking. This tutorial provides an overview of recently proposed measurement techniques for beam and mobility management in mmWave cellular networks, and gives insights into the design of accurate, reactive and robust control schemes suitable for a 3GPP NR cellular network. We will illustrate that the best strategy depends on the specific environment in which the nodes are deployed, and give guidelines to inform the optimal choice as a function of the system parameters.

Key facts. Cited by 33 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Apr 2018.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 7; 2023: 2; 2024: 4; 2025: 10; 2026: 5.

33 papers.

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  1. 2022Deep Learning on Multimodal Sensor Data at the Wireless Edge for Vehicular Networkcited by 15
  2. 2025A Multi-Task Foundation Model for Wireless Channel Representation Using Contrastive and Masked Autoencoder Learningcited by 15
  3. 2022Pervasive Machine Learning for Smart Radio Environments Enabled by Reconfigurable Intelligent Surfacescited by 12
  4. 2021Colosseum: Large-Scale Wireless Experimentation Through Hardware-in-the-Loop Network Emulationcited by 11
  5. 2021Deep Learning Assisted Calibrated Beam Training for Millimeter-Wave Communication Systemscited by 5
  6. 2021Network-Aware 5G Edge Computing for Object Detection: Augmenting Wearables to "See" More, Farther and Fastercited by 3
  7. 2022Beam Management in Ultra-dense mmWave Network via Federated Reinforcement Learning: An Intelligent and Secure Approachcited by 3
  8. 2022Fast Beam Alignment via Pure Exploration in Multi-armed Banditscited by 3
  9. 2025Explainable and Robust Millimeter Wave Beam Alignment for AI-Native 6G Networkscited by 3
  10. 2022Massive MIMO Beam Management in Sub-6 GHz 5G NRcited by 2
  11. 2025Digital Twin-Assisted Explainable AI for Robust Beam Prediction in mmWave MIMO Systemscited by 2
  12. 2021Learning-Based UE Classification in Millimeter-Wave Cellular Systems With Mobilitycited by 1
21 more
  1. 2022Beam Management with Orientation and RSRP using Deep Learning for Beyond 5G Systemscited by 1
  2. 2022Efficient Beam Search for Initial Access Using Collaborative Filteringcited by 1
  3. 2023Hierarchical ML Codebook Design for Extreme MIMO Beam Managementcited by 1
  4. 2024Neural Codebook Design for Network Beam Managementcited by 1
  5. 2025Simplicity is Key: An Unsupervised Pretraining Approach for Sparse Radio Channelscited by 1
  6. 2026QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networkscited by 1
  7. 2026GSBF: Gaussian Splatting for Environment-Aware Beamformingcited by 1
  8. 2021On Single-User Interactive Beam Alignment in Next Generation Systems: A Deep Learning Viewpointcited by 0
  9. 2023Deep Learning and Image Super-Resolution-Guided Beam and Power Allocation for mmWave Networkscited by 0
  10. 2024Autonomous Self-Trained Channel State Prediction Method for mmWave Vehicular Communicationscited by 0
  11. 2024Remote Detection of Applications for Improved Beam Tracking in mmWave/sub-THz 5G/6G Systemscited by 0
  12. 2024Early-Scheduled Handover Preparation in 5G NR Millimeter-Wave Systemscited by 0
  13. 2025GPS-Aided Deep Learning for Beam Prediction and Tracking in UAV mmWave Communicationcited by 0
  14. 2025CWGAN-GP Augmented CAE for Jamming Detection in 5G-NR in Non-IID Datasetscited by 0
  15. 2025Efficient Beam Selection for ISAC in Cell-Free Massive MIMO via Digital Twin-Assisted Deep Reinforcement Learningcited by 0
  16. 2025Causal Beam Selection for Reliable Initial Access in AI-driven Beam Managementcited by 0
  17. 2025CAR-BRAINet: Sub-6GHz Aided Spatial Adaptive Beam Prediction with Multi Head Attention for Heterogeneous Vehicular Networkscited by 0
  18. 2025Meta-Learning Multi-armed Bandits for Beam Tracking in 5G and 6G Networkscited by 0
  19. 2026Toward Resilient 5G Networks: Comparative Analysis of Federated and Centralized Learning for RF Jamming Detectioncited by 0
  20. 2026Multi-perspective Imbalance-Conscious 6G Beamforming Optimization and Performancecited by 0
  21. 2026BeamRMX: Radiation-Pattern-Driven Learning for Generalizable Beam Radio Map Prediction and Beam Managementcited by 0