6G Wireless Channel Measurements and Models: Trends and Challenges
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Abstract (arXiv)
In this article, we first present our vision on the application scenarios, performance metrics, and potential key technologies of the sixth generation (6G) wireless communication networks. Then, 6G wireless channel measurements, characteristics, and models are comprehensively surveyed for all frequency bands and all scenarios, focusing on millimeter wave (mmWave), terahertz (THz), and optical wireless communication channels under all spectrums, satellite, unmanned aerial vehicle (UAV), maritime, and underwater acoustic communication channels under global coverage scenarios, and high-speed train (HST), vehicle-to-vehicle (V2V), ultra-massive multiple-input multiple-output (MIMO), orbital angular momentum (OAM), and industry Internet of things (IoT) communication channels under full application scenarios. Future research challenges on 6G channel measurements, a general standard 6G channel model framework, channel measurements and models for intelligent reflection surface (IRS) based 6G technologies, and artificial intelligence (AI) enabled channel measurements and models are also given.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 8 Dec 2020.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 4; 2025: 3; 2026: 1.
10 papers.
- 2022SlimFL: Federated Learning with Superposition Coding over Slimmable Neural Networkscited by 6
- 2024LinFormer: A Linear-based Lightweight Transformer Architecture For Time-Aware MIMO Channel Predictioncited by 6
- 2025CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priorscited by 6
- 2024Cross-domain Learning Framework for Tracking Users in RIS-aided Multi-band ISAC Systems with Sparse Labeled Datacited by 4
- 2024Large Vision Model-Enhanced Digital Twin with Deep Reinforcement Learning for User Association and Load Balancing in Dynamic Wireless Networkscited by 4
- 2025Large AI Model for Delay-Doppler Domain Channel Prediction in 6G OTFS-Based Vehicular Networkscited by 2
- 2025The Role, Trends, and Applications of Machine Learning in Undersea Communication: A Bangladesh Perspectivecited by 1
- 2022Simulation of machine learning-based 6G systems in virtual worldscited by 0
- 2024EM-GANSim: Real-time and Accurate EM Simulation Using Conditional GANs for 3D Indoor Scenescited by 0
- 2026Transform-Invariant Generative Ray Path Sampling for Efficient Radio Propagation Modelingcited by 0
- 2026Transform-Invariant Generative Ray Path Sampling for Efficient Radio Propagation Modeling2 Mar 2026
- 2025CKMDiff: A Generative Diffusion Model for CKM Construction via Inverse Problems with Learned Priors24 Apr 2025
- 2025Large AI Model for Delay-Doppler Domain Channel Prediction in 6G OTFS-Based Vehicular Networks3 Mar 2025
- 2025The Role, Trends, and Applications of Machine Learning in Undersea Communication: A Bangladesh Perspective1 Mar 2025
- 2024LinFormer: A Linear-based Lightweight Transformer Architecture For Time-Aware MIMO Channel Prediction28 Oct 2024
- 2024Large Vision Model-Enhanced Digital Twin with Deep Reinforcement Learning for User Association and Load Balancing in Dynamic Wireless Networks10 Oct 2024
- 2024EM-GANSim: Real-time and Accurate EM Simulation Using Conditional GANs for 3D Indoor Scenes27 May 2024
- 2024Cross-domain Learning Framework for Tracking Users in RIS-aided Multi-band ISAC Systems with Sparse Labeled Data10 May 2024
- 2022Simulation of machine learning-based 6G systems in virtual worlds15 Apr 2022
- 2022SlimFL: Federated Learning with Superposition Coding over Slimmable Neural Networks26 Mar 2022