World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
50
Citations
8655
World Ranking
2841
National Ranking
471

Overview

Jun Fang is affiliated with the University of Electronic Science and Technology of China. Their research primarily spans the fields of Engineering and Computer Science, with a strong focus on Electrical and Electronic Engineering, Aerospace Engineering, Artificial Intelligence, Computer Networks and Communications, and Computational Mechanics.

The scientist has contributed extensively to topics related to advanced wireless communication and antenna technologies. Key areas of their work include:

  • Advanced Wireless Communication Technologies
  • Antenna Design and Analysis
  • Advanced MIMO Systems Optimization
  • Indoor and Outdoor Localization Technologies
  • Millimeter-Wave Propagation and Modeling
  • Sparse and Compressive Sensing Techniques
  • Antenna Design and Optimization

Jun Fang's publication record includes papers in several notable scientific venues. Frequent publication outlets include:

  • arXiv (Cornell University)
  • IEEE Transactions on Signal Processing
  • IEEE Wireless Communications Letters
  • IEEE Transactions on Wireless Communications
  • IEEE Transactions on Vehicular Technology

Representative recent papers authored or co-authored by Jun Fang are:

  • "Terahertz Multi-User Massive MIMO With Intelligent Reflecting Surface: Beam Training and Hybrid Beamforming," 2021, IEEE Transactions on Vehicular Technology
  • "Joint Transceiver and Large Intelligent Surface Design for Massive MIMO mmWave Systems," 2020, IEEE Transactions on Wireless Communications
  • "Deep Learning-Based Spectrum Sensing in Cognitive Radio: A CNN-LSTM Approach," 2020, IEEE Communications Letters
  • "Joint Waveform and Beamforming Design for RIS-Aided ISAC Systems," 2023, IEEE Signal Processing Letters
  • "Unsupervised Deep Spectrum Sensing: A Variational Auto-Encoder Based Approach," 2020, IEEE Transactions on Vehicular Technology

The scientist's frequent collaborators include:

  • Hongbin Li
  • Peilan Wang
  • Bin Wang
  • Zhi Chen
  • Boyu Ning

Best Publications

  • Intelligent Reflecting Surface-Assisted Millimeter Wave Communications: Joint Active and Passive Precoding Design

    Peilan Wang;Jun Fang;Xiaojun Yuan;Zhi Chen

  • Compressed Channel Estimation for Intelligent Reflecting Surface-Assisted Millimeter Wave Systems

    Peilan Wang;Jun Fang;Huiping Duan;Hongbin Li

  • Multiantenna-Assisted Spectrum Sensing for Cognitive Radio

    Pu Wang;Jun Fang;Ning Han;Hongbin Li

  • Intelligent Reflecting Surface-Assisted Millimeter Wave Communications: Joint Active and Passive Precoding Design

    Peilan Wang;Jun Fang;Xiaojun Yuan;Zhi Chen

  • Low-Rank Tensor Decomposition-Aided Channel Estimation for Millimeter Wave MIMO-OFDM Systems

    Zhou Zhou;Jun Fang;Linxiao Yang;Hongbin Li

  • Pattern-Coupled Sparse Bayesian Learning for Recovery of Block-Sparse Signals

    Jun Fang;Yanning Shen;Hongbin Li;Pu Wang

  • Terahertz Multi-User Massive MIMO With Intelligent Reflecting Surface: Beam Training and Hybrid Beamforming

    Boyu Ning;Zhi Chen;Wenrong Chen;Yiming Du

  • Improving Physical Layer Security Using UAV-Enabled Mobile Relaying

    Qian Wang;Zhi Chen;Weidong Mei;Jun Fang

  • Intelligent Power Control for Spectrum Sharing in Cognitive Radios: A Deep Reinforcement Learning Approach

    Xingjian Li;Jun Fang;Wen Cheng;Huiping Duan

  • Super-Resolution Compressed Sensing for Line Spectral Estimation: An Iterative Reweighted Approach

    Jun Fang;Feiyu Wang;Yanning Shen;Hongbin Li

  • Millimeter Wave Channel Estimation via Exploiting Joint Sparse and Low-Rank Structures

    Xingjian Li;Jun Fang;Hongbin Li;Pu Wang

  • Channel Estimation for TDD/FDD Massive MIMO Systems With Channel Covariance Computing

    Hongxiang Xie;Feifei Gao;Shi Jin;Jun Fang

  • Joint Transceiver and Large Intelligent Surface Design for Massive MIMO MmWave Systems

    Peilan Wang;Jun Fang;Linglong Dai;Hongbin Li

  • Deep Learning-Based Spectrum Sensing in Cognitive Radio: A CNN-LSTM Approach

    Jiandong Xie;Jun Fang;Chang Liu;Xuanheng Li

  • Deep Clustering by Gaussian Mixture Variational Autoencoders With Graph Embedding

    Linxiao Yang;Ngai-Man Cheung;Jiaying Li;Jun Fang

  • Joint Waveform and Beamforming Design for RIS-Aided ISAC Systems

    Unknown

  • Super-Resolution Channel Estimation for MmWave Massive MIMO With Hybrid Precoding

    Chen Hu;Linglong Dai;Talha Mir;Zhen Gao

  • Beamforming Optimization for Intelligent Reflecting Surface Assisted MIMO: A Sum-Path-Gain Maximization Approach

    Boyu Ning;Zhi Chen;Wenjie Chen;Jun Fang

  • Channel Estimation for Millimeter-Wave Multiuser MIMO Systems via PARAFAC Decomposition

    Zhou Zhou;Jun Fang;Linxiao Yang;Hongbin Li

  • Spherical Wave Channel and Analysis for Large Linear Array in LoS Conditions

    Zhou Zhou;Xiang Gao;Jun Fang;Zhi Chen

  • Global and local structure preserving sparse subspace learning

    Nan Zhou;Yangyang Xu;Hong Cheng;Jun Fang

  • Low-Rank Covariance-Assisted Downlink Training and Channel Estimation for FDD Massive MIMO Systems

    Jun Fang;Xingjian Li;Hongbin Li;Feifei Gao

  • Data-Driven-Based Analog Beam Selection for Hybrid Beamforming Under mm-Wave Channels

    Yin Long;Zhi Chen;Jun Fang;Chintha Tellambura

  • Distributed Adaptive Quantization for Wireless Sensor Networks: From Delta Modulation to Maximum Likelihood

    Jun Fang;Hongbin Li

  • Applications of the SRV constraint in broadband pattern synthesis

    Huiping Duan;Boon Poh Ng;Chong Meng Samson See;Jun Fang

  • Joint Channel Estimation and Multiuser Detection for Uplink Grant-Free NOMA

    Yang Du;Binhong Dong;Wuyong Zhu;Pengyu Gao

  • Block-Sparsity-Based Multiuser Detection for Uplink Grant-Free NOMA

    Yang Du;Cong Cheng;Binhong Dong;Zhi Chen

Frequent Co-Authors

Hongbin Li
Hongbin Li Stevens Institute of Technology
Zhi Chen
Zhi Chen University of Kentucky
Shaoqian Li
Shaoqian Li University of Electronic Science and Technology of China
Ying-Chang Liang
Ying-Chang Liang University of Electronic Science and Technology of China
Feifei Gao
Feifei Gao Tsinghua University
Athina P. Petropulu
Athina P. Petropulu Rutgers, The State University of New Jersey
Rick S. Blum
Rick S. Blum Lehigh University
Linglong Dai
Linglong Dai Tsinghua University
Hing Cheung So
Hing Cheung So City University of Hong Kong
Wei Zhang
Wei Zhang University of New South Wales

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