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能量信息深度融合的移动网络架构及其技术挑战

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5G的大规模部署伴随着网络能耗呈指数级增长,与此同时,国家提出了"碳达峰"与"碳中和"的"双碳"目标,因此移动网络的节能减排已刻不容缓.然而,一方面随着人工智能等技术的发展,未来6G网络中计算类业务预期将迎来大幅增长;另一方面,实现绿色低碳需要提升可再生能源的利用率,但绿色新能源供能不稳难以保证服务质量.为应对以上挑战,本文提出一种能量与信息服务深度融合的低碳网络架构,通过构建一个协调异质资源的智能控制面,充分利用并调度移动网络中泛在的算力、通信和储能,在保证6G个性化业务服务质量要求的同时,以期大幅降低网络能耗与碳排放.本文同时还讨论了该架构下的调度机制设计以及可能的未来研究方向.
Deep integration of the energy and information:network architecture and technology challenges
The large-scale deployment of 5G is accompanied by an exponential increase in network energy consumption.At the same time,the country has put forward the"dual-carbon"strategic requirements of"carbon peak"and"carbon neutrality",so it is urgent to achieve energy-saving and emission reduction in mobile networks.However,on the one hand,with the development of technologies such as artificial intelligence,computation-intensive services are expected to see significant growth in future 6G networks.On the other hand,achieving green and low-carbon goals requires improving the utilization of renewable energy,but the instability of green energy supply makes it difficult to guarantee service quality.To address these challenges,this paper proposes a low-carbon network architecture that deeply integrates energy and information services.By building an intelligent control plane that coordinates heterogeneous resources,it fully utilizes and schedules the ubiquitous computing,communication,and energy storage in mobile networks.The goal is to greatly reduce network energy consumption and carbon emissions while ensuring the quality of personalized services in 6G.This paper also discusses the design of scheduling mechanisms under this architecture and possible future research directions.

6Glow carbonenergy savingcommunications and computing integrationgreen energy

周盛、孙宇璇、姜之源、龚杰、常征、牛志升

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清华大学电子工程系,北京 100084

北京交通大学电子信息工程学院,北京 100044

上海大学通信与信息工程学院,上海 200444

中山大学计算机学院,广州 510275

电子科技大学计算机科学与工程学院,成都 611731

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6G 低碳 节能 通信计算融合 绿色能源

国家自然科学基金国家自然科学基金国家自然科学基金国家自然科学基金国家自然科学基金

6234110862301024622713006217148162071105

2024

中国科学F辑
中国科学院,国家自然科学基金委员会

中国科学F辑

CSTPCD北大核心
影响因子:1.438
ISSN:1674-5973
年,卷(期):2024.54(4)
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