移动通信2025，Vol.49Issue(5)：63-66,103,5.DOI:10.3969/j.issn.1006-1010.20250324-0003
无线环境知识表示方法研究——工业互联网场景的应用
Research on Representation Methods for Wireless Environment Knowledge:Application in IIoT Scenarios
摘要
Abstract
Wireless Environment Knowledge(WEK)aims to characterize the mapping relationship between environmental features and wireless channels,playing a critical role in predicting dynamic channel characteristics and optimizing communication resource allocation.The Industrial Internet of Things(IIoT),which integrates internet technologies with traditional industrial systems,features large-scale scenarios,dense device distribution,abundant metallic equipment,diverse material properties,and frequency-dependent signal transmission characteristics,resulting in communication environments influenced by multiple factors.Accurate characterization of environmental properties facilitates precise path loss(PL)prediction in complex electromagnetic environments such as IIoT,thereby improving communication quality and reliability.To address the multidimensional characteristics of IIoT scenarios,this study first analyzes the impact of device materials on signal transmission,constructing material-specific knowledge coefficients based on electromagnetic parameters and frequency-dependent properties.Subsequently,a WEK representation method tailored for IIoT scenarios is proposed,which quantifies the contributions of scattering effects(reflection,diffraction,and blockage)to received signal power using location-aware data and knowledge coefficients.A neural network(NN)-based PL prediction framework integrating WEK is further developed.Finally,a simplified indoor IIoT scenario is simulated to validate the effectiveness of the proposed knowledge coefficients and WEK representation.关键词
无线环境知识/工业互联网/知识系数/路损预测Key words
wireless environment knowledge/industrial internet of things/knowledge coefficient/path loss prediction分类
电子信息工程引用本文复制引用
张兆灵,于力,张宇翔,王嘉琳,张建华,姜涛..无线环境知识表示方法研究——工业互联网场景的应用[J].移动通信,2025,49(5):63-66,103,5.基金项目
国家重点研发计划"复杂高动态环境与多维多尺度信道关联映射及数据库构建"(2023YFB2904803) （2023YFB2904803）
国家自然科学基金"基于传播环境信息表征的分层信道在线智能预测方法及应用"(62401084) （62401084）
国家自然科学基金"基于共享多径簇的感知通信一体化信道传播特性与建模方法研究"(62201087) （62201087）
