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作 者:李露 李福昌[2] Li Lu;Li Fuchang(China Unicom Research Institute,Beijing 100048,China)
机构地区:[1]中国联通研究院,北京100048 [2]中国联通研究院无线技术研究中心,北京100048
出 处:《信息通信技术》2021年第5期52-57,共6页Information and communications Technologies
摘 要:文章提出4G/5G基站智能节能方案,用于移动通信行业降低基站设备能耗,节省网络运营成本及碳排放。文章提出的解决方案是基于人工智能技术,通过强化学习、联邦学习等智能化算法,从网络层面统一实施多制式协同的4G/5G基站节能策略。同时,文章提出通过细化预测精度及预测时长来增加智能节能算法的准确性方法及评估结果。文章提出的智能节能方案能够准确预测基站的业务量、灵活调整节能策略,使得智能节能方案可在多制式网络、不同小区场景下智能适配,在不影响业务体验的前提下达到更好的节能效果。This paper proposes 4G and 5G base station intelligent energy-saving solutions,which are used in the mobile communications industry to reduce the energy consumption of base station equipment and save network operating costs and carbon emissions.The solution proposed in the paper is based on artificial intelligence technology.The solution implements multi-networks coordination 4G/5G base station energy-saving strategy from the network level,through reinforcement learning,federated learning and other intelligent algorithms.At the same time,this paper proposes methods and evaluation results to increase the accuracy of smart energy-saving algorithms by refining the prediction accuracy and prediction duration.The intelligent energy-saving solution proposed in the paper can accurately predict the traffic volume of the base station and flexibly adjust energy-saving strategies,so that the intelligent energy-saving solution can be intelligently adapted in multi-networks and different cell scenarios,in order to achieve better energy saving without affecting the business experience.
分 类 号:TN929.5[电子电信—通信与信息系统]
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