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Dr Chang Liu
Postdoctoral Fellow

Dr Chang Liu

Engineering
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
E-mail
chang.liu19@unsw.edu.au
  • Journal articles | 2023
    Lu X; Yan S; Yang W; Liu C; Ng DWK, 2023, 'Short-Packet Covert Communication in Interweave Cognitive Radio Networks', IEEE Transactions on Vehicular Technology, vol. 72, pp. 2649 - 2654, http://dx.doi.org/10.1109/TVT.2022.3210991
    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, vol. 21, pp. 10315 - 10334, http://dx.doi.org/10.1109/TWC.2022.3183300
    Journal articles | 2022
    Li S; Yuan W; Liu C; Wei Z; Yuan J; Bai B; Ng DWK, 2022, 'A Novel ISAC Transmission Framework Based on Spatially-Spread Orthogonal Time Frequency Space Modulation', IEEE Journal on Selected Areas in Communications, vol. 40, pp. 1854 - 1872, http://dx.doi.org/10.1109/JSAC.2022.3155538
    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 | 2022
    Liu C; Yuan W; Li S; Liu X; Li H; Ng DWK; Li Y, 2022, 'Learning-Based Predictive Beamforming for Integrated Sensing and Communication in Vehicular Networks', IEEE Journal on Selected Areas in Communications, vol. 40, pp. 2317 - 2334, http://dx.doi.org/10.1109/JSAC.2022.3180803
    Journal articles | 2021
    Chen J; Liu J; Liu C; Zhang J; Han B, 2021, 'Underwater Target Recognition based on Multi-Decision LOFAR Spectrum Enhancement: A Deep Learning Approach', , http://arxiv.org/abs/2104.12362v1
    Journal articles | 2021
    Hu S; Wei Z; Cai Y; Liu C; Ng DWK; Yuan J, 2021, 'Robust and Secure Sum-Rate Maximization for Multiuser MISO Downlink Systems with Self-Sustainable IRS', IEEE Transactions on Communications, vol. 69, pp. 7032 - 7049, http://dx.doi.org/10.1109/TCOMM.2021.3097140
    Journal articles | 2021
    Liu C; Liu X; Wei Z; Hu S; Ng DWK; Yuan J, 2021, 'Deep Learning-Empowered Predictive Beamforming for IRS-Assisted Multi-User Communications', , http://arxiv.org/abs/2104.12309v1
    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 | 2021
    Liu C; Yuan W; Li S; Liu X; Li H; Ng DWK; Li Y, 2021, 'Learning-based Predictive Beamforming for Integrated Sensing and Communication in Vehicular Networks', , http://arxiv.org/abs/2108.11540v2
    Journal articles | 2021
    Liu C; Yuan W; Wei Z; Liu X; Ng DWK, 2021, 'Location-Aware Predictive Beamforming for UAV Communications: A Deep Learning Approach', IEEE Wireless Communications Letters, vol. 10, pp. 668 - 672, http://dx.doi.org/10.1109/LWC.2020.3045150
    Journal articles | 2021
    Liu X; Liu C; Li Y; Vucetic B; Ng DWK, 2021, 'Deep Residual Learning-Assisted Channel Estimation in Ambient Backscatter Communications', IEEE Wireless Communications Letters, vol. 10, pp. 339 - 343, http://dx.doi.org/10.1109/LWC.2020.3030222
    Journal articles | 2021
    Zhang Q; Ge L; Zhang R; Metternicht GI; Liu C; Du Z, 2021, 'Towards a deep-learning-based framework of sentinel-2 imagery for automated active fire detection', Remote Sensing, vol. 13, pp. 4790 - 4790, http://dx.doi.org/10.3390/rs13234790
    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
    Journal articles | 2020
    Xie J; Fang J; Liu C; Li X, 2020, 'Deep Learning-Based Spectrum Sensing in Cognitive Radio: A CNN-LSTM Approach', IEEE Communications Letters, vol. 24, pp. 2196 - 2200, http://dx.doi.org/10.1109/LCOMM.2020.3002073
    Journal articles | 2020
    Xie J; Fang J; Liu C; Yang L, 2020, 'Unsupervised Deep Spectrum Sensing: A Variational Auto-Encoder Based Approach', IEEE Transactions on Vehicular Technology, vol. 69, pp. 5307 - 5319, http://dx.doi.org/10.1109/TVT.2020.2982203
    Journal articles | 2020
    Yuan W; Liu C; Liu F; Li S; Ng DWK, 2020, 'Learning-Based Predictive Beamforming for UAV Communications with Jittering', IEEE Wireless Communications Letters, vol. 9, pp. 1970 - 1974, http://dx.doi.org/10.1109/LWC.2020.3009951
    Journal articles | 2019
    Liu C; Wang J; Liu X; Liang Y-C, 2019, 'Maximum Eigenvalue-Based Goodness-of-Fit Detection for Spectrum Sensing in Cognitive Radio', IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, vol. 68, pp. 7747 - 7760, http://dx.doi.org/10.1109/TVT.2019.2923648
    Journal articles | 2019
    Liu C; Wang J; Liu X; Liang YC, 2019, 'Deep CM-CNN for Spectrum Sensing in Cognitive Radio', IEEE Journal on Selected Areas in Communications, vol. 37, pp. 2306 - 2321, http://dx.doi.org/10.1109/JSAC.2019.2933892
    Journal articles | 2019
    Xie J; Liu C; Liang YC; Fang J, 2019, 'Activity Pattern Aware Spectrum Sensing: A CNN-Based Deep Learning Approach', IEEE Communications Letters, vol. 23, pp. 1025 - 1028, http://dx.doi.org/10.1109/LCOMM.2019.2910176
    Journal articles | 2018
    Zhang X; Zhang Y; Liu C; Jia H, 2018, 'Low-Complexity Detection Algorithms for Spatial Modulation MIMO Systems', JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING, vol. 2018, http://dx.doi.org/10.1155/2018/4034625
    Journal articles | 2017
    Liu C; Li H; Wang J; Jin M, 2017, 'Optimal eigenvalue weighting detection for multi-antenna cognitive radio networks', IEEE Transactions on Wireless Communications, vol. 16, pp. 2083 - 2096, http://dx.doi.org/10.1109/TWC.2016.2632711
    Journal articles | 2016
    Chen J; Liu C; Li H; Li X; Li S, 2016, 'A Categorized Resource Sharing Mechanism for Device-to-Device Communications in Cellular Networks', Mobile Information Systems, vol. 2016, http://dx.doi.org/10.1155/2016/5894752
    Journal articles | 2016
    Liu C; Li H; Jin M, 2016, 'Blind Central-Symmetry-Based Feature Detection for Spatial Spectrum Sensing', IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, vol. 65, pp. 10147 - 10152, http://dx.doi.org/10.1109/TVT.2016.2550608
    Journal articles | 2015
    Liu C; Li M; Jin M-L, 2015, 'Blind Energy-Based Detection for Spatial Spectrum Sensing', IEEE WIRELESS COMMUNICATIONS LETTERS, vol. 4, pp. 98 - 101, http://dx.doi.org/10.1109/LWC.2014.2377233
  • Conference Papers | 2022
    Cai Y; Yuan W; Wei Z; Liu C; Hu S; Kwan Ng DW, 2022, 'Trajectory Design and Resource Allocation for UAV-Enabled Data Collection in Wireless Sensor Networks with 3D Blockages', in 2022 1st International Conference on 6G Networking, 6GNet 2022, IEEE, presented at 2022 1st International Conference on 6G Networking (6GNet), 06 July 2022 - 08 July 2022, http://dx.doi.org/10.1109/6GNet54646.2022.9830200
    Preprints | 2022
    Chen J; Liu C; Xie J; An J; Huang N, 2022, Time-Frequency Mask Aware Bi-directional LSTM: A Deep Learning Approach for Underwater Acoustic Signal Separation, http://arxiv.org/abs/2202.04405v1
    Conference Papers | 2022
    Hu S; Liu C; Wei Z; Cai Y; Kwan Ng DW; Yuan J, 2022, 'Beamforming Design for Intelligent Reflecting Surface-Enhanced Symbiotic Radio Systems', in IEEE International Conference on Communications, IEEE, pp. 2651 - 2657, presented at ICC 2022 - IEEE International Conference on Communications, 16 May 2022 - 20 May 2022, http://dx.doi.org/10.1109/ICC45855.2022.9838902
    Preprints | 2022
    Liu C; Li S; Yuan W; Liu X; Ng DWK, 2022, Predictive Precoder Design for OTFS-Enabled URLLC: A Deep Learning Approach, http://arxiv.org/abs/2212.13651v1
    Preprints | 2022
    Liu C; Liu X; Li S; Yuan W; Ng DWK, 2022, Deep CLSTM for Predictive Beamforming in Integrated Sensing and Communication-enabled Vehicular Networks, http://arxiv.org/abs/2209.12368v1
    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
    Conference Papers | 2022
    Liu C; Yuan W; Li S; Liu X; Ng DWK; Li Y, 2022, 'Predictive Beamforming for Integrated Sensing and Communication in Vehicular Networks: A Deep Learning Approach', in IEEE International Conference on Communications, IEEE, pp. 1948 - 1954, presented at ICC 2022 - IEEE International Conference on Communications, 16 May 2022 - 20 May 2022, http://dx.doi.org/10.1109/ICC45855.2022.9839000
    Preprints | 2022
    Liu C; Yuan W; Li S; Liu X; Ng DWK; Li Y, 2022, Predictive Beamforming for Integrated Sensing and Communication in Vehicular Networks: A Deep Learning Approach, http://arxiv.org/abs/2202.03811v1
    Conference Papers | 2021
    Liu C; Liu X; Kwan Ng DW; Yuan J, 2021, 'Deep Residual Network Empowered Channel Estimation for IRS-Assisted Multi-User Communication Systems', in IEEE International Conference on Communications, IEEE, http://dx.doi.org/10.1109/ICC42927.2021.9500708