B5G系统中基于无线大数据的新兴技术

doi:10.13190/j.jbupt.2018-258

北京邮电大学学报 ›› 2018, Vol. 41 ›› Issue (5): 52-61.doi: 10.13190/j.jbupt.2018-258

B5G系统中基于无线大数据的新兴技术

张四海¹, 张建华², 陈颖³, 朱近康¹

1. 中国科学技术大学中国科学院无线光电通信重点实验室, 合肥 230027;
2. 北京邮电大学网络与交换技术国家重点实验室, 北京 100876;
3. 浙江大学信息与电子工程学院英国约克大学-浙江大学认知网络与绿色通信联合实验室, 杭州 310058

收稿日期:2018-10-19 出版日期:2018-10-28 发布日期:2018-11-20
作者简介:张四海(1974-),男,副教授,E-mail:shzhang@ustc.edu.cn.
基金资助:
国家自然科学基金重点项目（61631018）；科技部重大科技专项项目（2018ZX03001031）；北京市自然科学基金重点项目（L172030）

Wireless Big Data Enabled Emerging Technologies for Beyond 5G System

ZHANG Si-hai¹, ZHANG Jian-hua², CHEN Ying³, ZHU Jin-kang¹

1. Key Laboratory of Wireless-Optical Communications, CAS, University of Science and Technology of China, Hefei 230027, China;
2. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China;
3. York-Zhejiang Laboratory for Cognitive Radio and Green Communications, College of Information Science & Electronic Engineering, Zhejiang University, Hangzhou 310058, China

Received:2018-10-19 Online:2018-10-28 Published:2018-11-20
Supported by:

摘要/Abstract

摘要： 基于无线大数据（WBD）和人工智能（AI）的通信技术（涵盖物理层、网络层和应用层）被认为是最有前景的研究之一.该领域三项有趣的研究工作包括信道建模、大规模接入和网络拓扑设计.信道建模部分从机器学习在无线信道建模中应用的可行方法入手，介绍了参数估计中的主流方法，即信道多径聚类，该方法对于未来的研究具有重要意义.大规模接入部分关注分形现象及其在无线网络中的可能应用，主要研究了分形D2D社交网络的最大容量.网络拓扑设计部分介绍了如何利用移动用户的动态移动性特征来减少超密集网络（UDN）中的无线资源消耗.这些工作被认为是5G后有发展前景的研究领域，无线大数据分析为相关研究的未来工作提供了可能线索.

关键词: 无线大数据, Beyond 5G, 大规模接入, 信道建模, 移动性识别

Abstract: The fifth generation of mobile communications system (5G) will be deployed in 2020 and provide diverse communication capabilities, but the promising future of beyond 5G is surely necessary for the communication requirements incurred by fast growing information technology in the next decade. Among several roadmaps toward beyond 5G, wireless big data (WBD) plus artificial intelligence (AI) based communication technology, which covers physical layer, network layer and application layer, is considered as one of the most promising ways. Along with this thought, some emerging research works have been published, which further stimulate more researcher to pay more attention in this area. This paper introduces three interesting works toward this aim, which covers channel modelling, huge access, and network topology design. The channel modelling part starts with the feasible ways to apply machine learning to wireless channel modelling, and presents the prevailing methods in parameter estimation, channel multipath clustering, which is of great importance for future research. The huge access part focuses on fractal phenomenon and its possible applications in wireless networks. After introducing the basic concept, this part investigates the maximum capacity fractal D2D social networks. The network topology design part proposes an interesting topic, whose motivation is to utilize the dynamic mobility features of mobile users to decrease the wireless resource consumption in ultra dense networks (UDN). In summary, these three works are considered as promising topics in beyond 5G, which combines wireless big data analysis and may shed light on related future research.

Key words: wireless big data, beyond 5G, huge access, channel modelling, mobility recognition

中图分类号:

TN929.53

张四海, 张建华, 陈颖, 朱近康. B5G系统中基于无线大数据的新兴技术[J]. 北京邮电大学学报, 2018, 41(5): 52-61.

ZHANG Si-hai, ZHANG Jian-hua, CHEN Ying, ZHU Jin-kang. Wireless Big Data Enabled Emerging Technologies for Beyond 5G System[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2018, 41(5): 52-61.

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B5G系统中基于无线大数据的新兴技术

Wireless Big Data Enabled Emerging Technologies for Beyond 5G System

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