# A Survey of Beam Management for mmWave and THz Communications Towards 6G

arXiv: https://arxiv.org/abs/2308.02135 · HTML: https://mlsanity.com/paper/2308.02135/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Aug 2023.

## Built on by (most cited first, 21 of 21)

- [Artificial General Intelligence (AGI)-Native Wireless Systems: A Journey Beyond 6G](https://mlsanity.com/paper/2405.02336/) (2024)
- [A MIMO Wireless Channel Foundation Model via CIR-CSI Consistency](https://mlsanity.com/paper/2502.11965/) (2025)
- [Survey of Graph Neural Network for Internet of Things and NextG Networks](https://mlsanity.com/paper/2405.17309/) (2024)
- [M2BeamLLM: Multimodal Sensing-empowered mmWave Beam Prediction with Large Language Models](https://mlsanity.com/paper/2506.14532/) (2025)
- [VOMTC: Vision Objects for Millimeter and Terahertz Communications](https://mlsanity.com/paper/2409.09330/) (2024)
- [Explainable and Robust Millimeter Wave Beam Alignment for AI-Native 6G Networks](https://mlsanity.com/paper/2501.17883/) (2025)
- [Multi-Modality Sensing in mmWave Beamforming for Connected Vehicles Using Deep Learning](https://mlsanity.com/paper/2504.06173/) (2025)
- [Digital Twin-Assisted Explainable AI for Robust Beam Prediction in mmWave MIMO Systems](https://mlsanity.com/paper/2507.14180/) (2025)
- [Hierarchical ML Codebook Design for Extreme MIMO Beam Management](https://mlsanity.com/paper/2312.02178/) (2023)
- [Multi-Modal Sensing Aided mmWave Beamforming for V2V Communications with Transformers](https://mlsanity.com/paper/2509.11112/) (2025)
- [Multi-User Beamforming with Deep Reinforcement Learning in Sensing-Aided Communication](https://mlsanity.com/paper/2505.05956/) (2025)
- [GPS-Aided Deep Learning for Beam Prediction and Tracking in UAV mmWave Communication](https://mlsanity.com/paper/2505.17530/) (2025)
- [Secure mmWave Beamforming with Proactive-ISAC Defense Against Beam-Stealing Attacks](https://mlsanity.com/paper/2508.02856/) (2025)
- [Physics-Informed Neural Networks for MIMO Beam Map and Environment Reconstruction](https://mlsanity.com/paper/2510.21238/) (2025)
- [Self-Localizing MIMO Beam Mapping with Continuously Evolving Channel Memory](https://mlsanity.com/paper/2511.17007/) (2025)
- [RadioMapMotion: A Dataset and Baseline for Proactive Spatio-Temporal Radio Environment Prediction](https://mlsanity.com/paper/2511.17526/) (2025)
- [Refined Bayesian Optimization for Efficient Beam Alignment in Intelligent Indoor Wireless Environments](https://mlsanity.com/paper/2512.00036/) (2025)
- [Multi-Modal Sensing and Fusion in mmWave Beamforming for Connected Vehicles: A Transformer Based Framework](https://mlsanity.com/paper/2602.13606/) (2026)
- [Look Once, Beam Twice: Camera-Primed Real-Time Double-Directional mmWave Beam Management for Vehicular Connectivity](https://mlsanity.com/paper/2605.05071/) (2026)
- [CFM-Bench: A Unified Multi-Domain, Multi-Task Benchmark for Channel Foundation Models](https://mlsanity.com/paper/2607.14975/) (2026)
- [Wireless Foundation Models: State-of-the-Art and Open Challenges](https://mlsanity.com/paper/2609.04707/) (2026)

## Abstract (arXiv)

Communication in millimeter wave (mmWave) and even terahertz (THz) frequency bands is ushering in a new era of wireless communications. Beam management, namely initial access and beam tracking, has been recognized as an essential technique to ensure robust mmWave/THz communications, especially for mobile scenarios. However, narrow beams at higher carrier frequency lead to huge beam measurement overhead, which has a negative impact on beam acquisition and tracking. In addition, the beam management process is further complicated by the fluctuation of mmWave/THz channels, the random movement patterns of users, and the dynamic changes in the environment. For mmWave and THz communications toward 6G, we have witnessed a substantial increase in research and industrial attention on artificial intelligence (AI), reconfigurable intelligent surface (RIS), and integrated sensing and communications (ISAC). The introduction of these enabling technologies presents both open opportunities and unique challenges for beam management. In this paper, we present a comprehensive survey on mmWave and THz beam management. Further, we give some insights on technical challenges and future research directions in this promising area.