A Predictive 6G Network with Environment Sensing Enhancement: From Radio Wave Propagation Perspective

Gaofeng Nie, Jianhua Zhang, Yuxiang Zhang, Li Yu, Zhen Zhang, Yutong Sun, Lei Tian, Qixing Wang and Liang Xia
China Communications
Publish Year: 2022

Abstract: In order to support the future digital society, sixth generation (6G) network faces the challenge to work efficiently and flexibly in a wider range of scenarios. The traditional way of system design is to sequentially get the electromagnetic wave propagation model of typical scenarios firstly and then do the network design by simulation offline, which obviously leads to a 6G network lacking of adaptation to dynamic environments. Recently, with the aid of sensing enhancement, more environment information can be obtained. Based on this, from radio wave propagation perspective, we propose a predictive 6G network with environment sensing enhancement, the electromagnetic wave propagation characteristics prediction enabled network (EWaveNet), to further release the potential of 6G. To this end, a prediction plane is created to sense, predict and utilize the physical environment information in EWaveNet to realize the electromagnetic wave propagation characteristics prediction timely. A two-level closed feedback workflow is also designed to enhance the sensing and prediction ability for EWaveNet. Several promising application cases of EWaveNet are analyzed and the open issues to achieve this goal are addressed finally.

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