Semantic Characteristics and Modeling of Wireless Channels for 6G

ZHANG Zheng-yu; HE Rui-si; YANG Mi; ZHANG Xue-jian; QI Zi-yi; YUAN Yuan; AI Bo

doi:10.12263/DZXB.20240595

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Semantic Characteristics and Modeling of Wireless Channels for 6G

Special Focus: Recipient of CIE Outstanding Doctoral Dissertation | 更新时间：2025-12-08

- Semantic Characteristics and Modeling of Wireless Channels for 6G
- ACTA ELECTRONICA SINICA Vol. 53, Issue 1, Pages: 14-23(2025)
- 作者机构：
  
  北京交通大学电子信息工程学院，北京 100044
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China(62271037)
- DOI：10.12263/DZXB.20240595
  CLC： TN.92;
- Received：25 June 2024，
  
  Revised：2024-10-21，
  
  Published：25 January 2025
- 稿件说明：
移动端阅览
张正宇, 何睿斯, 杨汨, 等. 面向6G的无线信道语义特征及建模[J]. 电子学报, 2025, 53(01): 14-23.

ZHANG Zheng-yu, HE Rui-si, YANG Mi, et al. Semantic Characteristics and Modeling of Wireless Channels for 6G[J]. Acta Electronica Sinica, 2025, 53(01): 14-23.
张正宇, 何睿斯, 杨汨, 等. 面向6G的无线信道语义特征及建模[J]. 电子学报, 2025, 53(01): 14-23. DOI：10.12263/DZXB.20240595

ZHANG Zheng-yu, HE Rui-si, YANG Mi, et al. Semantic Characteristics and Modeling of Wireless Channels for 6G[J]. Acta Electronica Sinica, 2025, 53(01): 14-23. DOI：10.12263/DZXB.20240595

摘要

随着移动通信技术的发展演进，6G（6th-Generation）网络作为新一代智能化数字信息基础设施，将不再仅聚焦信号的传输和复现，更需要基于电磁传播过程实现对周围环境的高效感知和理解，从而获取信道语义知识，协助智能通信体的预测、决策、波束成形等.因此，相较于传统信道而言，赋予无线信道模型对物理环境的语义理解、重构、表达能力，已成为智能无线信道模型的重要特征.本文提出了一种无线信道语义的分析和建模方法，将信道语义定义为状态语义、行为语义和事件语义3种层级，分别对应信道瞬态多径、信道时变轨迹和信道拓扑结构.此外，基于车载通感一体化（Integrated Sensing And Communication，ISAC）信道测量系统，开展了28 GHz下面向信道语义表征的无线信道测量，基于实测数据对信道语义进行解构、标识、建模，重点分析了3种不同语义下的信道多径分布特性，完成了语义导向的信道生成，结果表明信道语义模型能够在生成较准确信道的同时，表达更丰富的语义信息.本文工作是在语义层面上探索智能信道建模的新方法，通过深入挖掘无线信道的内在语义特征，促进通信系统在理解和认知环境方面的能力，从而提高通信效率和质量.

Abstract

With the development of mobile communication technology

6G (6th-Generation) networks

as the next generation of intelligent digital information infrastructure

will no longer only focus on the transmission and reproduction of signals. Instead

they will need to achieve efficient perception and understanding of the surrounding environment based on the electromagnetic propagation

acquire semantic knowledge to assist intelligent communication agents in prediction

decision

beamforming

and more. Therefore

compared to traditional channel models

improving wireless channel models with the ability to understand

reconstruct

and express the physical environment’s semantics has become an important characteristic of intelligent wireless channel models. This paper proposes a method for semantic analysis and modeling of wireless channels

which includes three levels of semantics: state semantics

behavior semantics

and event semantics

corresponding to the instant multipath of the channel

the time-varying trajectory of the channel

and the topological structure of the channel

respectively. In addition

based on the vehicular integrated sensing and communication (ISAC) channel measurement platform

this paper conducts semantic-oriented wireless channel measurements at 28 GHz. The channel semantics are decomposed

identified

and modeled based on the measured data

with a focus on analyzing the multipath distribution characteristics of the channel under three different semantics

and completing the semantic-guided channel generation. The results show that the channel semantics model can generate more accurate channels while expressing richer semantic information. The work in this paper explores new methods for intelligent channel modeling at the semantic level

promoting the ability of communication systems to understand and recognize the environment by deeply mining semantic features of wireless channels

thereby improving communication efficiency and quality.

关键词

Keywords

references

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