Dr Chang Liu
Postdoctoral Fellow

Dr Chang Liu

Electrical Engineering and Telecommunications

Chang Liu received the Ph.D. degree in signal and information processing from Dalian University of Technology, China, in 2017 and was a joint Ph.D. from the University of Tennessee, Knoxville, USA. He was a postdoctoral research fellow with the University of Electronic Science and Technology of China. He is currently a Research Fellow with the University of New South Wales, Sydney, Australia. To date, he has published more than 40 journal and conference papers and 4 journal papers were listed among the top 50 popular papers ranked by IEEE Xplore. He is currently serving as a Lead Guest Editor of Future Internet and a foundation member of IEEE Comsoc special interest group on orthogonal time frequency space (OTFS). 

His research interests include machine learning for communications, integrated sensing and communication (ISAC), OTFS, intelligent reflecting surface (IRS)-assisted communications, unmanned aerial vehicle (UAV) communications, Internet of Things (IoT), and cognitive radio. 

Personal homepage: https://cliuwcom.weebly.com

  • Journal articles | 2022
    Cai Y; Wei Z; Hu S; Liu C; Ng DWK; Yuan J, 2022, 'Resource Allocation and 3D Trajectory Design for Power-Efficient IRS-Assisted UAV-NOMA Communications', IEEE Transactions on Wireless Communications, pp. 1 - 1, http://dx.doi.org/10.1109/TWC.2022.3183300
    Journal articles | 2022
    Liu C; Liu X; Ng DWK; Yuan J, 2022, 'Deep Residual Learning for Channel Estimation in Intelligent Reflecting Surface-Assisted Multi-User Communications', IEEE Transactions on Wireless Communications, vol. 21, pp. 898 - 912, http://dx.doi.org/10.1109/TWC.2021.3100148
    Journal articles | 2021
    Liu C; Wei Z; Ng DWK; Yuan J; Liang YC, 2021, 'Deep Transfer Learning for Signal Detection in Ambient Backscatter Communications', IEEE Transactions on Wireless Communications, vol. 20, pp. 1624 - 1638, http://dx.doi.org/10.1109/TWC.2020.3034895
    Journal articles | 2020
    Liu C; Liu X; Wei Z; Kwan Ng DW; Yuan J; Liang YC, 2020, 'Deep Transfer Learning-Assisted Signal Detection for Ambient Backscatter Communications', 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings, vol. 2020-January, http://dx.doi.org/10.1109/GLOBECOM42002.2020.9348274
  • Preprints | 2022
    Liu C; Liu X; Wei Z; Ng DWK; Schober R, 2022, Scalable Predictive Beamforming for IRS-Assisted Multi-User Communications: A Deep Learning Approach, http://arxiv.org/abs/2211.12644v1