摘要
近年来,人工智能技术已被应用于无线通信领域,以解决传统无线通信技术面对信息爆炸和万物互联等新发展趋势所遇到的瓶颈问题。首先介绍深度学习、深度强化学习和联邦学习三类具有代表性的人工智能技术;然后通过对这三类技术在无线通信中的无线传输、频谱管理、资源配置、网络接入、网络及系统优化5个方面的应用进行综述,分析和总结它们在解决无线通信问题时的原理、适用性、设计方法和优缺点;最后围绕存在的局限性指出智能无线通信技术的未来发展趋势和研究方向,期望为无线通信领域的后续研究提供帮助和参考。
In recent years,artificial intelligence(AI)has been applied to wireless communications,in order to address the challenges introduced by data explosion and Internet of everything.Firstly,three core technologies of AI were introduced,including deep learning,deep reinforcement learning,and federated learning.Then,an overview of their applications on wireless communications was provided,from the aspects of wireless transmission,spectrum management,resource allocation,network access,network and system optimization.Based on the overview,the principle,applicability,design methodology,pros and cons on applying AI technologies to solve wireless communication problems were analyzed and summarized.Regarding the existed limitations,the future development trends and research directions on intelligent wireless communication technologies were pointed out,to hopefully provide useful help and reference for the future research in this field.
作者
梁应敞
谭俊杰
Dusit Niyato
LIANG Yingchang;TAN Junjie;Dusit Niyato(National Key Laboratory of Science and Technology on Communications,University of Electronic Science and Technology of China,Chengdu 611731,China;School of Computer Science and Engineering,Nanyang Technological University,Singapore 639798,Singapore)
出处
《通信学报》
EI
CSCD
北大核心
2020年第7期1-17,共17页
Journal on Communications
基金
国家自然科学基金资助项目(No.61631005,No.U1801261)
国家重点研发计划基金资助项目(No.2018YFB1801105)
高等学校学科创新引智计划基金资助项目(No.B20064)。
关键词
人工智能
无线通信
深度学习
深度强化学习
联邦学习
artificial intelligence
wireless communication
deep learning
deep reinforcement learning
federated learning
