Towards 6G Digital Twin Channel Using Radio Environment Knowledge Pool

TL;DR

This paper proposes a Radio Environment Knowledge Pool (REKP) to improve 6G digital twin channels by accurately modeling environment-channel relationships, enhancing performance, reducing costs, and addressing open challenges in wireless communication.

Contribution

Introduction of REKP as a novel framework for constructing and updating environment-channel knowledge to enable more accurate 6G digital twin channels.

Findings

REKP effectively models environment-channel relationships in 6G scenarios.

Using REKP improves digital twin accuracy and system performance.

REKP reduces costs and enhances trustworthiness in 6G wireless systems.

Abstract

The digital twin channel (DTC) is crucial for 6G wireless autonomous networks as it replicates 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, with its core function being to construct and store as much knowledge between the environment and channels as possible. 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, how to utilize REKP to address open issues in the 6G wireless communication system is discussed, including enhancing performance, reducing costs, and keeping a trustworthy DTC.