上海电子信息职业技术学院通信与信息工程学院,上海 201411
[ "李兰兰(1974- ),女,博士,上海电子信息职业技术学院通信与信息工程学院高级工程师,主要研究方向为5G/6G通信、人工智能、元宇宙。" ]
收稿:2025-02-28,
修回:2025-04-29,
纸质出版:2025-05-20
移动端阅览
李兰兰.通感融算赋能的空天地一体化网络架构及关键技术[J].电信科学,2025,41(05):29-42.
LI Lanlan.Architecture and key technologies of the space-air-ground integrated network empowered by integrated sensing, computing and communication[J].Telecommunications Science,2025,41(05):29-42.
李兰兰.通感融算赋能的空天地一体化网络架构及关键技术[J].电信科学,2025,41(05):29-42. DOI: 10.11959/j.issn.1000-0801.2025124.
LI Lanlan.Architecture and key technologies of the space-air-ground integrated network empowered by integrated sensing, computing and communication[J].Telecommunications Science,2025,41(05):29-42. DOI: 10.11959/j.issn.1000-0801.2025124.
随着6G通信技术的蓬勃发展,通感融算(integrated sensing,computing and communication,ISCC)正成为推动空天地一体化网络演进的重要动力。从ISCC的核心概念出发,讨论了其在空天地一体化网络中的关键作用,提出了一种基于ISCC赋能的两级管理与编排的网络架构,并对该架构的关键技术进行了分析。最后,总结了当前该领域所面临的挑战,并展望了未来的发展趋势,以期为6G时代空天地一体化网络的构建提供参考和借鉴。
With the rapid development of 6G communication technology
integrated sensing
computing
and communication (ISCC) has become a key driving force in the evolution of space-air-ground integrated network. Starting from the core concept of ISCC
its critical role in space-air-ground integrated network was discussed
and a multi-level management and orchestration network architecture empowered by ISCC was proposed. Key technologies of this architecture were analyzed. Finally
the current challenges faced in this field were summarized
and future development trends were prospected
aiming to provide valuable reference and insights for the construction of space-air-ground integrated network in the 6G era.
IMT-2030(6G)推进组 . 6G典型场景和关键能力白皮书 [R ] . 2022 .
IMT-2030(6G)推进组 . 6G网络架构愿景与关键技术展望白皮书 [R ] . 2021 .
孙韶辉 , 戴翠琴 , 徐晖 , 等 . 面向6G的星地融合一体化组网研究 [J ] . 重庆邮电大学学报(自然科学版) , 2021 , 33 ( 6 ): 891 - 901 .
SUN S H , DAI C Q , XU H , et al . Survey on satellite-terrestrial integration networking towards 6G [J ] . Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition) , 2021 , 33 ( 6 ): 891 - 901 .
Federal Communications Commission . Expanding flexible use of the 12 .2-12.7 GHz band[EB ] . 2021.
PIN TAN D K , HE J , LI Y C , et al . Integrated sensing and communication in 6G: motivations, use cases, requirements, challenges and future directions [C ] // Proceedings of the 2021 1st IEEE International Online Symposium on Joint Communications & Sensing (JC&S) . Piscataway : IEEE Press , 2021 : 1 - 6 .
BAYESTEH A , HE J , CHEN Y , et al . Integrated sensing and communication (ISAC)-from concept to practice [J ] . Communications of HUAWEI RESEARCH , 2022 ( 11 ): 4 - 25 .
Ericsson . Baldemair . Integrated sensing and communication[EB ] . 2024 .
袁硕 . 星地融合无线网络的资源调配理论与方法 [D ] . 北京 : 北京邮电大学 , 2024 .
YUAN S . Theories and methods of resource allocation in intergrated satellite-terrestrial wireless networks [D ] . Beijing : Beijing University of Posts and Telecommunications , 2024 .
SALEM H , QUAMAR M M , MANSOOR A , et al . Data-driven integrated sensing and communication: recent advances, challenges, and future prospects [J ] . arXiv preprint , 2023 : 2308 .09090.
孙耀华 , 彭木根 , 赵亚飞 , 等 . 低轨卫星互联网: 从星地融合迈向通导遥一体化 [J ] . 北京邮电大学学报 , 2024 , 47 ( 6 ): 69 - 98 .
SUN Y H , PENG M G , ZHAO Y F , et al . Low earth orbit satellite network: from satellite-terrestrial convergence to the integration of communication, navigation and sensing [J ] . Journal of Beijing University of Posts and Telecommunications , 2024 , 47 ( 6 ): 69 - 98 .
周宇柯 . 面向大规模低轨卫星网络的星地链路规划技术研究 [D ] . 北京 : 北京邮电大学 , 2024 .
ZHOU Y K . Research on satellite-to-ground link planning schemes for large-scale LEO Networks [D ] . Beijing : Beijing University of Posts and Telecommunications , 2024 .
3GPP. Study on using satellite access in 5G: 3GPP TR 22.822 V16.0.0 [S ] . 2018 .
3GPP. Study on management aspects of next generation network architecture and features: 3GPP TR 28.802 V15.0.0 [S ] . 2018 .
3GPP. Study on architecture aspects for using satellite access in 5G: 3GPP TR 23.737 V17.2.0 [S ] . 2021 .
KAFLE V P , SEKIGUCHI M , ASAEDA H , et al . Integrated network control architecture for terrestrial and non-terrestrial network convergence [C ] // Proceedings of the IEEE Communications Standards Magazine . Piscataway : IEEE Press , 2024 : 12 - 19 .
CHEN C , LIAO Z , JU Y , et al . Hierarchical domain-based multicontroller deployment strategy in SDN-enabled space-air-ground integrated network [J ] . IEEE Transactions on Aerospace and Electronic Systems , 2022 , 58 ( 6 ): 4864 - 4879 .
LIU X N , ZHANG H J , SUN K , et al . AI-driven integration of sensing and communication in the 6G era [J ] . IEEE Network , 2024 , 38 ( 3 ): 210 - 217 .
GRAFF A , CHEN Y , GONZÁLEZ-PRELCIC N , et al . Deep learning-based link configuration for radar-aided multiuser mmWave vehicle-to-infrastructure communication [J ] . IEEE Transactions on Vehicular Technology , 2023 , 72 ( 6 ): 7454 - 7468 .
CHEN Y , GRAFF A , GONZÁLEZ-PRELCIC N , et al . Radar aided mmWave vehicle-to-infrastructure link configuration using deep learning [C ] // Proceedings of the 2021 IEEE Global Communications Conference (GLOBECOM) . Piscataway : IEEE Press , 2021 : 1 - 6 .
MU J S , GONG Y , ZHANG F P , et al . Integrated sensing and communication-enabled predictive beamforming with deep learning in vehicular networks [J ] . IEEE Communications Letters , 2021 , 25 ( 10 ): 3301 - 3304 .
LIU C , YUAN W J , LI S Y , et al . Predictive beamforming for integrated sensing and communication in vehicular networks: a deep learning approach [C ] // Proceedings of the ICC 2022 - IEEE International Conference on Communications . Piscataway : IEEE Press , 2022 : 1948 - 1954 .
ELBIR A M , MISHRA K V , CHATZINOTAS S . Terahertz-band joint ultra-massive MIMO radar-communications: model-based and model-free hybrid beamforming [J ] . IEEE Journal of Selected Topics in Signal Processing , 2021 , 15 ( 6 ): 1468 - 1483 .
LIU P X , ZHU G X , JIANG W , et al . Vertical federated edge learning with distributed integrated sensing and communication [J ] . IEEE Communications Letters , 2022 , 26 ( 9 ): 2091 - 2095 .
ZHANG Z B , CHANG Q , XING J , et al . Deep-learning methods for integrated sensing and communication in vehicular networks [J ] . Vehicular Communications , 2023 , 40 : 100574 .
ZHENG L , LOPS M , WANG X D . Adaptive interference removal for uncoordinated radar/communication coexistence [J ] . IEEE Journal of Selected Topics in Signal Processing , 2018 , 12 ( 1 ): 45 - 60 .
WANG M , CHEN P , CAO Z X , et al . Reinforcement learning-based UAVs resource allocation for integrated sensing and communication (ISAC) system [J ] . Electronics , 2022 , 11 ( 3 ): 441 .
HOSSAIN M A , XIANG A , KIANI A , et al . AI-assisted E2E network slicing for integrated sensing and communication in 6G networks [J ] . IEEE Internet of Things Journal , 2024 , 11 ( 6 ): 10627 - 10634 .
WANG C , LIU L , JIANG C X , et al . Incorporating distributed DRL into storage resource optimization of space-air-ground integrated wireless communication network [J ] . IEEE Journal of Selected Topics in Signal Processing , 2022 , 16 ( 3 ): 434 - 446 .
JIANG F , ZHANG L , SUN C Y , et al . Clustering and resource allocation strategy for D2D multicast networks with machine learning approaches [J ] . China Communications , 2021 , 18 ( 1 ): 196 - 211 .
杨帅斌 , 张昱 , 卢为党 . 面向6G的卫星通信感知一体化网络及关键技术 [J ] . 中兴通讯技术 , 2024 , 30 ( 5 ): 16 - 23 .
YANG S B , ZHANG Y , LU W D . Satellite integrated sensing and network for 6G and its key technologies [J ] . ZTE Technology Journal , 2024 , 30 ( 5 ): 16 - 23 .
LIU F , MASOUROS C , PETROPULU A P , et al . Joint radar and communication design: applications, state-of-the-art, and the road ahead [J ] . IEEE Transactions on Communications , 2020 , 68 ( 6 ): 3834 - 3862 .
CHEN X , FENG Z , WEI Z , et al . Code-division OFDM joint communication and sensing system for 6G machine-type communication [J ] . IEEE Internet of Things Journal , 2021 , 8 ( 15 ): 12093 - 12105 .
O-RAN . O-RAN: towards an open and smart RAN white paper [R ] . 2018 .
刘雪芳 , 毛伟灏 , 杨清海 . 基于深度强化学习的空天地一体化网络资源分配算法 [J ] . 电子与信息学报 , 2024 , 46 ( 7 ): 2831 - 2841 .
LIU X F , MAO W H , YANG Q H . A resource allocation algorithm for space-air-ground integrated network based on deep reinforcement learning [J ] . Journal of Electronics & Information Technology , 2024 , 46 ( 7 ): 2831 - 2841 .
0
浏览量
3289
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621