Radio Environment Knowledge Pool for 6G Digital Twin Channel

The digital twin channel (DTC) is crucial for 6G wireless autonomous networks as it repli-cates the wireless channel fading states in 6G air interface transmissions. It is well known that the physical environment influences channels. A key task for accurately twinning channels in complex 6G scenarios is establishing precise relationships between the environment and the channels. In this article, the radio environment knowledge pool (REKP) is proposed to abstract the channel propagation process from diverse environment and channel data, facilitating efficient compression and intelligent comprehension of the underlying mapping rules of the channel. Firstly, the research progress related to DTC is summarized, and a comparative analysis of these achievements on key indicators in digital twin is conducted, proposing the challenges faced in knowledge construction. Secondly, instructions on how to construct and update REKP are given. Then, a typical case is presented to demonstrate the great potential of REKP in enabling DTC. Finally, the utilization of REKP to address open issues in the 6G wireless communication system is discussed, including het-erogeneous datasets, knowledge updating strategies, and trustworthy DTC.