人工智能在5G网络的应用和标准化进展被引量：6

Application and Standardization Progress of AI in 5G Network

下载PDF

导出

摘要首先探讨了在5G网络中引入AI的必要性和存在的问题。然后介绍AI技术的发展概况以及AI在5G网络中的典型应用。最后介绍了目前国际标准化组织3GPP和ITU-T在AI与5G结合上的标准化研究进展。通过介绍AI在5G的发展可知5G网络智能化不仅要从AI算法研究方面实现突破,还需要有相关的政策法规来严格保护用户隐私。 Firstly, the necessity and issues of introducing AI into 5G network are analyzed. Then, the developmental trend of AI technology and typical application of AI in 5G network are expounded. Finally, the standardization research progress in the AI and 5G of international standardization organizations including 3GPP and ITU-T are introduced. By elaborating the development of AI in the 5G era, intelligent 5G network not only requires the breakthrough in AI algorithms, but also needs related policies and regulations to strictly protect user privacy.

作者王胡成陈山枝艾明 WANG Hucheng;CHEN Shanzhi;AI Ming(Datang Mobile Communications Equipment Co.,Ltd.,Beijing 100083,China;State Key Laboratory of Wireless Mobile Communications,China Academy of Telecommunication Technology,Beijing 100191,China)

机构地区大唐移动通信设备有限公司电信科学技术研究院无线移动通信国家重点实验室

出处《移动通信》 2019年第6期76-81,共6页 Mobile Communications

关键词 5G 人工智能应用场景标准化 5G artifi cial intelligence use case standardization

分类号 TN929.5 [电子电信—通信与信息系统]

引文网络
相关文献

参考文献4

1邹蕾,张先锋.人工智能及其发展应用[J].信息网络安全,2012(2):11-13. 被引量：201
2李建会.论布鲁克斯的无表征智能理论[J].自然辩证法研究,2007,23(7):9-13. 被引量：4
3刘建伟,刘媛,罗雄麟.半监督学习方法[J].计算机学报,2015,38(8):1592-1617. 被引量：127
4刘忠,李海红,刘全.强化学习算法研究[J].计算机工程与设计,2008,29(22):5805-5809. 被引量：10

二级参考文献36

1王鸿斌,张立毅,胡志军.人工神经网络理论及其应用[J].山西电子技术,2006(2):41-43. 被引量：34
2Tom M Mitchell.Machine learning[M].Beijing, China:Machine Press,2004:263-280.
3Dayan P.The convergence of TD (λ) for general λ[J].Machine Learning, 1992(8):341-362.
4Kaelbling L P, Littman M L,Moore A W.Reinforcement learning: A survey[J].Joumal of Artificial Intelligence Research, 1996(4): 237-285.
5Watins P Dyna. Q_leaming [J]. Machine Learning, 1992,8 (3): 279-292.
6Moor A W, Atkeson C G.Prioritized sweeping: Reinforcement learning with less data and less real time[J].Machine Learning, 1993,13:103-130.
7Hu J, Wellman M ENash Q-learning for general-sum stochastic games [J]. Journal of Machine Learning Research, 2003 (4): 1039-1069.
8Badtke S J,Barto R G.Linear least-squares algorithms for temporal differenee learning [J]. Machine Learning, 1996,22 (1-3): 33-57.
9Bowling M.Convergence and no-regret in multiagent learning [C].Advances in Naural Information Processing Systems,2004.
10Winfried Ilg,Karsten Bems.A learning architecture based on for adaptive control of the walking machine LAURON[J].Robot and Autonomous System, 1995,15:323-334.