6G通感算一体化体系架构与关键技术

吴子君; 张海君; 马旭; 任语铮

doi:10.11999/JEIT241151

6G通感算一体化体系架构与关键技术

doi: 10.11999/JEIT241151

北京科技大学北京 100083

基金项目: 国家自然科学基金(62225103, U22B2003)，北京市自然科学基金(L241008)，中央高校基本科研业务费专项资金(FRF-TP-22-002C2)，国家资助博士后研究人员计划资助(GZB20230057)

详细信息

作者简介:
吴子君：女，博士生，研究方向为6G移动通信和人工智能技术

张海君：男，教授，研究方向为6G移动通信、B5G行业应用、数字孪生和人工智能

马旭：男，博士生，研究方向为6G移动通信和NTN网络

任语铮：女，特聘副教授，研究方向为6G移动通信、车联网、工业互联网

通讯作者:
张海君　zhanghaijun@ustb.edu.cn

中图分类号: TN926
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- 文章访问数: 262
- HTML全文浏览量: 120
- PDF下载量: 71
- 被引次数: 0
出版历程
- 收稿日期: 2024-12-30
- 修回日期: 2025-04-01
- 网络出版日期: 2025-04-07
- 刊出日期: 2025-04-01

System Architecture and Key Technologies of 6G Integrated Sensing, Communication, and Computing

Beijing University of Science and Technology, Beijing 100083, China

Funds: The National Natural Science Foundation of China (62225103 and U22B2003), Beijing Natural Science Foundation (L241008), The Fundamental Research Funds for the Central Universities (FRF-TP-22-002C2), The Postdoctoral Fellowship Program of CPSF (GZB20230057)

摘要

摘要: 通感算一体化网络作为第六代移动通信系统的重要发展方向，融合了通信、感知和计算功能，为未来智能网络的高效协同提供了技术支撑。该文首先介绍了通感智能协同和云雾边算力协同技术，并结合区块链技术，研究了通感算一体化体系架构，提升了数据传输与存储的安全性。随后，深入分析了高精度感知与干扰管控方法，包括按需适配的高精度感知机制、双层优化频谱共享框架以及通感互干扰的优化策略。最后，围绕弹性接入与资源优化，探讨了人工智能驱动的资源分配框架和动态资源优化与调度策略，有效提升多维资源利用率和网络适应能力，满足未来高效、智能、安全的通感算一体化网络需求。
- 通感算一体化 /
- 资源分配 /
- 干扰管控 /
- 无线通信技术
Abstract: Significance The communication–sensing–computing integrated network, a central direction in the development of Sixth-Generation (6G) mobile communication systems, represents a shift toward intelligent network coordination. This architecture addresses key challenges in secure data transmission, efficient resource allocation, and intelligent network control. These capabilities are essential for supporting emerging applications in an era defined by pervasive connectivity and artificial intelligence. Progress This paper analyzes three key technologies of the communication–sensing–computing integrated network. First, a collaborative architecture integrating communication and sensing is proposed, which combines cloud–fog–edge computing and blockchain technologies to ensure secure data transmission and storage. Second, high-precision sensing and interference management are examined, including adaptive sensing mechanisms based on demand, a dual-layer optimized spectrum-sharing framework, and strategies for mitigating mutual interference in integrated systems. Third, Artificial Intelligence (AI)-driven frameworks for resource allocation are presented, including dynamic strategies for optimization and scheduling, which enhance multi-dimensional resource efficiency and improve network adaptability to support future intelligent, secure, and high-efficiency integrated networks. Conclusions The integrated architecture and methods presented in this paper form the technical foundation of the 6G communication–sensing–computing integrated network. The blockchain-enhanced framework provides robust security, whereas the adaptive sensing mechanisms and interference management strategies enable improved performance in complex network environments. The AI-driven resource allocation framework further enhances network operation by significantly improving resource utilization efficiency and adaptability. Prospects Future research on integrated communication–sensing–computing networks should focus on core technologies such as collaborative mechanisms across communication, sensing, and computing; heterogeneous data processing methods; and intelligent resource scheduling. These technologies are critical for addressing challenges related to resource optimization, interoperability, and dynamic adaptation in complex network environments. Through continued research and technological advancement, next-generation wireless systems aim to realize an efficient, reliable, and intelligent communication–sensing–computing integrated framework for 6G networks.
- Integrated sensing, communication, and computing /
- Resource allocation /
- Interference control /
- Wireless communications

HTML全文

图 1 6G典型应用场景下的通感算一体化网络

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图 2 通感算智能协同

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图 3 按需适配高精度感知技术

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图 4 通感一体化干扰管控

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图 5 AI驱动的通感算资源分配

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表 1 6G关键性能指标

目标关键指标	2022年欧洲网络安全与信息大会^[2,3]	ITU IMT-2030^[4]	5G美国/Next G联盟^[5,6]	华为^[8]	B5G联盟(日本)^[9]
峰值数据速率	1 Tb/s	50～200 Gbps	0.5～1 Tbps	1 Tbps	100～200 Gbps
用户数据速率	10 Gbps	300～500 Mbps	下行链路：达到1 Gbps 上行链路：达到1 Gbps	10～100 Gbps	10～100 Gbps
密度	10⁶设备/km²	10⁶～10⁸设备/km²	10⁶设备/km²	10⁶设备/km²	10⁶设备/km²
可靠性	>1×10^–8	～1×10^–5～1×10^–7	>1×10^–8	>1×10^–7	>1×10^–7
用户时延	<0.1 ms	0.1～1 ms	0.1～1 ms	0.1 ms	0.1～1 ms
移动性	<1 000 km/h	500～1 000 km/h	>500 km/h	/	达到1 000 km/h
定位精度	<1 cm	1～10 cm	1 mm～10 cm 六自由度的运动： (x,y,z)	室外：50 cm 室内：1 cm	1～2 cm

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