Electromagnetic intelligence twin via source-environment-field integration for 6G

CHENG Nan; SUN Ruijin; YIN Zhisheng; LEI Yuxin; LI Ming; SHEN Xuemin

doi:10.11959/j.issn.2096-3750.WLW26063

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Electromagnetic intelligence twin via source-environment-field integration for 6G

更新时间：2026-08-10

- Electromagnetic intelligence twin via source-environment-field integration for 6G
- Chinese Journal on Internet of Things (2026)
- 作者机构：
  
  1.西安电子科技大学通信工程学院，陕西西安 710071
  2.滑铁卢大学电子与计算机工程系，加拿大安大略省滑铁卢 N2L 3G1
- 作者简介：
- 基金信息：
  
  The Young Scientist Project of the National Key Research and Development Program of China(2024YFB2907500);The General Program of the National Natural Science Foundation of China(62571402);The TCL Young Scholars Program
- DOI：10.11959/j.issn.2096-3750.WLW26063
  CLC： TN92
- Received：20 May 2026，
  
  Revised：2026-07-30，
  
  Accepted：10 August 2026，
- 稿件说明：
移动端阅览
CHENG Nan, SUN Ruijin, YIN Zhisheng, et al. Electromagnetic intelligence twin via source-environment-field integration for 6G[J/OL]. Chinese Journal on Internet of Things, 2026.
DOI：

CHENG Nan, SUN Ruijin, YIN Zhisheng, et al. Electromagnetic intelligence twin via source-environment-field integration for 6G[J/OL]. Chinese Journal on Internet of Things, 2026. DOI： 10.11959/j.issn.2096-3750.WLW26063.

摘要

第六代移动通信技术（6G

sixth generation mobile communications）正推动无线网络从传统信息传输向环境感知与空间智能融合系统演进。电磁空间作为6G网络与物理环境交互的核心载体，其精准认知直接决定感知、通信与决策的协同效能，是实现6G网络按需服务的关键前提。然而，复杂电磁空间难以实现高精度、实时可预测的数字化表征，制约了6G网络电磁空间智能孪生技术的发展。传统建模方法难以兼顾精度、实时性与泛化性，且现有研究多聚焦辐射源（源）、传播环境（境）、电磁场（场）三要素中的单一要素，缺乏对三要素耦合关系的系统刻画。针对上述问题，提出了电磁空间智能孪生“源-境-场”一体化认知模型。该模型通过参数估计、行为识别等技术实现“源”的精细化表征，依托三维几何重构与电磁传播效应建模完成“境”的物理重构，采用多尺度策略与物理-数据融合方法开展“场”的孪生建模。进一步，本文从一体化认知视角对现有技术在三类协同链路中的作用进行归纳：可微射线追踪、神经辐射场及生成式电磁地图（RM

radio map）等现有技术主要可为“源、境到场”的正向预测环节提供方法支撑；源定位与参数反演方法可支撑“场、境到源”的反向求解；环境结构与电磁材质反演方法则可支撑“场、源到境”的逆向推演。然后，结合6G网络、空天地一体化通信、应急救援及国防安全等典型场景，探讨了电磁空间智能孪生的潜在应用。最后，本文总结了当前研究面临的主要挑战，并展望面向6G的电磁空间统一建模理论、物理约束数据驱动方法及与大模型协同演化的发展方向。

Abstract

Sixth generation mobile communications (6G) is driving the evolution of wireless networks from traditional information transmission toward integrated systems that combine environmental perception with spatial intelligence. As the central medium through which 6G networks interact with the physical environment

electromagnetic space and its precise cognition directly determines the synergistic efficiency of perception

communication

and decision making; thus

it serves as a critical prerequisite for realizing on demand services in 6G networks. However

the inherent complexity of electromagnetic space makes it challenging to achieve high precision

real-time

and predictable digital representations

thereby constraining the development of intelligent digital twin technologies for 6G electromagnetic environments. Traditional modeling approaches struggle to simultaneously balance accuracy

real-time performance

and generalizability; moreover

existing research often focuses on only one of the three fundamental elements-radiation sources (“Source”)

propagation environments (“Environment”)

and electromagnetic fields (“Field”)-without systematically characterizing their coupled relationships. To address these issues

an integrated “Source-Environment-Field” cognitive model for intelligent electromagnetic space twins was proposed. The model achieves a fine-grained representation of the “Source” through techniques such as parameter estimation and behavior recognition

completes the physical reconstruction of the “Environment” through 3D geometric reconstruction and electromagnetic propagation-effect modeling

and performs digital-twin modeling of the “Field” using multiscale strategies and physics-data fusion methods. Furthermore

from an integrated cognitive perspective

this paper summarizes the roles of existing techniques in three collaborative links: existing techniques such as differentiable ray tracing

neural radiance fields

and generative radio map (RM) can mainly support the “Source-Environment-to-Field” forward prediction; source localization and parameter inversion methods can support the “Field-Environment-to-Source” inverse solving; and environmental structure and electromagnetic material inversion methods can support the “Field-Source-to-Environment” reverse inference. Subsequently

the paper explores the potential applications of intelligent electromagnetic space twins across various typical scenarios

including 6G networks

integrated space-air-ground communication systems

emergency rescue operations

and national defense security. Finally

the paper summarizes the major challenges currently facing this field of research and outlines future directions for the development of unified electromagnetic space modeling theories

physics-constrained da-ta-driven methodologies

and collaborative evolutionary approaches involving large-scale models-all geared toward the 6G era.

关键词

Keywords

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Intelligent terminal identification technology toward 6G

Related Author

Yong XIAO

Jiwei HU

Liang LIAO

Jianxin LYU

Zegang BAI

Peng ZHANG

Yan XI

Tong ZHANG

Related Institution

FiberHome Telecommunication Technologies Co., Ltd.

Pengcheng Laboratory

Pazhou Lab (Huangpu)

Wuhan FiberHome Technical Service Co., Ltd.

Huazhong University of Science and Technology

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