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Channel Knowledge Maps for 6G Wireless Networks: Construction, Applications, and Future Challenges
LIU Xingchen, SUN Shu, TAO Meixia, KAUSHIK Aryan, YAN Hangsong
ZTE Communications    2025, 23 (2): 46-59.   DOI: 10.12142/ZTECOM.202502006
Abstract32)   HTML0)    PDF (1292KB)(19)       Save

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.

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Editorial: Special Topic onMachine Learning at Network Edges
TAO Meixia, HUANG Kaibin
ZTE Communications    2020, 18 (2): 1-1.   DOI: 10.12142/ZTECOM.202002001
Abstract193)   HTML312)    PDF (536KB)(214)       Save
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