An Overview of Wireless Communication Technology Using Deep Learning

被引:1
|
作者
Jiyu Jiao [1 ]
Xuehong Sun [1 ,2 ]
Liang Fang [1 ]
Jiafeng Lyu [1 ]
机构
[1] School of Physics and Electronic-Electrical Engineering, Ningxia University
[2] School of Information Engineering, Ningxia University
基金
中国国家自然科学基金;
关键词
D O I
暂无
中图分类号
TN92 [无线通信]; TP18 [人工智能理论];
学科分类号
080402 ; 080904 ; 0810 ; 081001 ; 081104 ; 0812 ; 0835 ; 1405 ;
摘要
with the development of 5G, the future wireless communication network tends to be more and more intelligent.In the face of new service demands of communication in the future such as superheterogeneous network, multiple communication scenarios, large number of antenna elements and large bandwidth, new theories and technologies of intelligent communication have been widely studied, among which Deep Learning(DL) is a powerful technology in artificial intelligence(AI).It can be trained to continuously learn to update the optimal parameters.This paper reviews the latest research progress of DL in intelligent communication, and emphatically introduces five scenarios including Cognitive Radio(CR), Edge Computing(EC), Channel Measurement(CM), End to end Encoder/Decoder(EED) and Visible Light Communication(VLC).The prospect and challenges of further research and development in the future are also discussed.
引用
收藏
页码:1 / 36
页数:36
相关论文
共 50 条
  • [1] An Overview of Wireless Communication Technology Using Deep Learning
    Jiao, Jiyu
    Sun, Xuehong
    Fang, Liang
    Lyu, Jiafeng
    CHINA COMMUNICATIONS, 2021, 18 (12) : 1 - 36
  • [2] Overview on intelligent wireless communication technology
    智能无线通信技术研究概况
    2020, Editorial Board of Journal on Communications (41): : 1 - 17
  • [3] Machine Learning for Wireless Communication: An Overview
    Cao, Zijian
    Zhang, Hua
    Liang, Le
    Li, Geoffrey Ye
    APSIPA TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING, 2022, 11 (01)
  • [4] An overview of smart antenna technology for wireless communication
    Bhobe, AU
    Perini, PL
    2001 IEEE AEROSPACE CONFERENCE PROCEEDINGS, VOLS 1-7, 2001, : 875 - 883
  • [5] Overview of wireless implantable energy supply and communication technology
    Zhang S.
    Qin Y.
    Kuang J.-M.
    Yang J.
    Xu J.
    Wang J.
    Liu Y.
    Recent Patents on Engineering, 2021, 15 (04)
  • [6] Machine Learning for Wireless Communication Channel Modeling: An Overview
    Saud Mobark Aldossari
    Kwang-Cheng Chen
    Wireless Personal Communications, 2019, 106 : 41 - 70
  • [7] Machine Learning for Wireless Communication Channel Modeling: An Overview
    Aldossari, Saud Mobark
    Chen, Kwang-Cheng
    WIRELESS PERSONAL COMMUNICATIONS, 2019, 106 (01) : 41 - 70
  • [8] Ambulatory Phonation Monitoring Using Wireless Headphones With Deep Learning Technology
    Han, Ji-Yan
    Wang, Chi-Te
    Li, Jia-Hui
    Lai, Ying-Hui
    IEEE SYSTEMS JOURNAL, 2023, 17 (03): : 4752 - 4762
  • [9] Online Deep Learning in Wireless Communication Systems
    Eisen, Mark
    Zhang, Clark
    Chamon, Luiz F. O.
    Lee, Daniel D.
    Ribeiro, Alejandro
    2018 CONFERENCE RECORD OF 52ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, 2018, : 1289 - 1293
  • [10] Enhanced algorithmic modelling and architecture in deep reinforcement learning based on wireless communication Fintech technology
    Upreti, Kamal
    Syed, Mohammad Haider
    Khan, Mohiuddin Ali
    Fatima, Huda
    Alam, Mohammad Shabbir
    Sharma, A. K.
    OPTIK, 2023, 272