Sixth-generation (6G) mobile communication networks are expected to have dense infrastructures, large antenna size, wide bandwidth, cost-effective hardware, diversified positioning methods, and enhanced intelligence. Such trends bring both new challenges and opportunities for the practical design of 6G. On one hand, acquiring channel state information (CSI) in real time for all wireless links becomes quite challenging in 6G. On the other hand, there would be numerous data sources in 6G containing high-quality location-tagged channel data, e.g., the estimated channels or beams between base station (BS) and user equipment (UE), making it possible to better learn the local wireless environment. By exploiting this new opportunity and for tackling the CSI acquisition challenge, there is a promising paradigm shift from the conventional environment-unaware communications to the new environment-aware communications based on the novel approach of channel knowledge map (CKM). This article aims to provide a comprehensive overview on environment-aware communications enabled by CKM to fully harness its benefits for 6G. First, the basic concept of CKM is presented, followed by the comparison of CKM with various existing channel inference techniques. Next, the main techniques for CKM construction are discussed, including both environment model-free and environment model-assisted approaches. Furthermore, a general framework is presented for the utilization of CKM to achieve environment-aware communications, followed by some typical CKM-aided communication scenarios. Finally, important open problems in CKM research are highlighted and potential solutions are discussed to inspire future work.

翻译：第六代（6G）移动通信网络预期具备密集基础设施、大规模天线阵列、宽频带、低成本硬件、多样化定位方法及增强的智能性。这些趋势为6G的实用设计既带来新挑战也创造新机遇。一方面，在6G中实时获取所有无线链路的信道状态信息（CSI）变得极具挑战性。另一方面，6G中大量数据源将包含高质量的位置标记信道数据（例如基站与用户设备间估计的信道或波束），从而可能更好地学习本地无线环境。利用这一新机遇并应对CSI获取挑战，有望实现从传统非感知环境通信向基于信道知识地图（CKM）这一新方法的感知环境通信的范式转变。本文旨在全面综述CKM赋能的感知环境通信，以充分发挥其对6G的优势。首先介绍CKM的基本概念，并将其与现有各类信道推断技术进行对比。随后讨论CKM构建的主要技术，包括无环境模型与有环境模型辅助两类方法。进一步提出利用CKM实现感知环境通信的通用框架，并展示若干典型CKM辅助通信场景。最后指出CKM研究中重要的开放性问题，并探讨潜在解决方案以启发未来研究。