Channel Knowledge Maps for 6G Wireless Networks: Construction, Applications, and Future Challenges

doi:10.12142/ZTECOM.202502006

ZTE Communications ›› 2025, Vol. 23 ›› Issue (2): 46-59.DOI: 10.12142/ZTECOM.202502006

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Channel Knowledge Maps for 6G Wireless Networks: Construction, Applications, and Future Challenges

LIU Xingchen¹, SUN Shu¹(), TAO Meixia¹, KAUSHIK Aryan², YAN Hangsong³

^1.School of Information Science and Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
^2.Department of Computing and Mathematics, Manchester Metropolitan University, Manchester M1 5GD, UK
^3.Hangzhou Institute of Technology, Xidian University, Hangzhou 311231, China

Received:2025-04-09 Online:2025-06-25 Published:2025-06-10
Contact: SUN Shu
About author:LIU Xingchen received his BS degree in information engineering from Southeast University, China in 2022, and MS degree in information and communication engineering from Shanghai Jiao Tong University, China in 2025. His research interests include ray tracing, channel modeling, and the application of artificial intelligence in wireless communications.
SUN Shu (shusun@sjtu.edu.cn) obtained her BS degree in applied physics from Shanghai Jiao Tong University (SJTU), China in 2012, and PhD degree in electrical engineering from New York University, USA in 2018, and held summer internship positions at Nokia Bell Labs, USA in 2014 and 2015. She worked as a system engineer at Intel Corporation, USA from 2018 to 2021. She is currently a tenure-track associate professor at SJTU. Her current research interests include channel modeling, millimeter-wave communications, integrated sensing and communication, and holographic MIMO. She received multiple international academic awards including the 2023 and 2017 IEEE Neil Shepherd Memorial Best Propagation Paper Awards, the 2017 Marconi Society Young Scholar Award, the IEEE VTC2016-Spring Best Paper Award, and the 2015 IEEE Donald G. Fink Award. She is an editor for various international journals.
TAO Meixia received her BS degree in electronic engineering from Fudan University, China in 1999, and PhD degree in electrical and electronic engineering from Hong Kong University of Science and Technology, China in 2003. She is currently a distinguished professor with the School of Information Science and Electronic Engineering at Shanghai Jiao Tong University, China. Her research interests include wireless edge learning, semantic communications, integrated communication-computing-sensing, and AI-based channel modeling and beamforming. She received the 2019 IEEE Marconi Prize Paper Award, the 2013 IEEE Heinrich Hertz Award for Best Communications Letters, the IEEE/CIC International Conference on Communications in China (ICCC) 2015 Best Paper Award, the International Conference on Wireless Communications and Signal Processing (WCSP) 2012 and 2022 Best Paper Awards, and the 2009 IEEE ComSoc Asia-Pacific Outstanding Young Researcher Award. She is an editor for various international journals.
Aryan KAUSHIK has been an associate professor with Manchester Metropolitan University, UK since 2024. He is a core member of the IEEE P1955 Standard on 6G-Empowering Robotics, Chair of the IEEE ComSoc ETI on ESIT, Co-Chair of the IEEE SIG on AITNTN, and an editor of 5 books published by Elsevier and Wiley. He also serves as an editor for several journals, such as IEEE Transactions on Communications, IEEE Transactions on Mobile Computing, IEEE Communications Surveys and Tutorials, IEEE OJCOMS (2023 and 2024 Best Editor Award), IEEE Communications Letters (2023 and 2024 Exemplary Editor), IEEE IoT Magazine, and IEEE CTN. He has delivered invited talks, keynote speeches, and tutorials at over 110 academic and industry events and conferences globally, including IEEE ICC 2024-2025, IEEE GLOBECOM 2023-2024. Additionally, he has served as the General Chair for over 30 workshops and special sessions, such as those at IEEE ICC 2024-2025 and IEEE GLOBECOM 2023-2025.
YAN Hangsong received his PhD degree in electrical engineering from New York University, USA in 2021. From 2021 to 2024, he was a senior research engineer with Huawei Technologies Co., Ltd, China, where he received various awards including the Company Future Star Award and the President’s Award in 5G & LTE FDD domain. He is currently an associate researcher with Hangzhou Institute of Technology, Xidian University, China. His research interests include massive MIMO related theories and applications, and satellite communications. He serves as a reviewer for multiple international journals and conferences, and has been recognized as an exemplary reviewer for IEEE Transactions on Communications and IEEE Wireless Communications Letters.
Supported by:
the National Natural Science Foundation of China(62431014);the National Natural Science Foundation of China(62271310);the Fundamental Research Funds for the Central Universities of China

Abstract

Abstract:

The advent of 6G wireless networks promises unprecedented connectivity, supporting ultra-high data rates, low latency, and massive device connectivity. However, these ambitious goals introduce significant challenges, particularly in channel estimation due to complex and dynamic propagation environments. This paper explores the concept of channel knowledge maps (CKMs) as a solution to these challenges. CKMs enable environment-aware communications by providing location-specific channel information, reducing reliance on real-time pilot measurements. We categorize CKM construction techniques into measurement-based, model-based, and hybrid methods, and examine their key applications in integrated sensing and communication (ISAC) systems, beamforming, trajectory optimization of unmanned aerial vehicles (UAVs), base station (BS) placement, and resource allocation. Furthermore, we discuss open challenges and propose future research directions to enhance the robustness, accuracy, and scalability of CKM-based systems in the evolving 6G landscape.

Key words: channel knowledge map, channel modeling, wireless communication, 6G

LIU Xingchen, SUN Shu, TAO Meixia, KAUSHIK Aryan, YAN Hangsong. Channel Knowledge Maps for 6G Wireless Networks: Construction, Applications, and Future Challenges[J]. ZTE Communications, 2025, 23(2): 46-59.

Figures/Tables 5

Figure 1 Illustration of environment knowledge enabled by channel knowledge map[9]: (a) path loss prediction and (b) beamforming

Figure 2 Example of channel knowledge map representation in a given region: (a) RMS delay spread map and (b) received power map

Figure 3 Comparison of measurement-driven CKM construction methods

Figure 4 Fingerprint localization using CGM in integrated sensing and communication systems

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Channel Knowledge Maps for 6G Wireless Networks: Construction, Applications, and Future Challenges

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