Nguyen Quang Hieu

About Me

I am a third-year Ph.D. student at School of Electrical and Data Engineering, University of Technology Sydney (UTS), Australia, working with Dr. Hoang Dinh and Dr. Diep Nguyen. Before joining UTS, I was a research assistant at Nanyang Technological University (NTU), Singapore, working with Prof. Dusit Niyato. I obtained my Bachelor’s degree in 2018 from Hanoi University of Science and Technology, Vietnam, under supervison of Dr. Nguyen Huu Thanh.

Research Interests

During my time at NTU Singapore, I spent most of my time exploring deep reinforcement learning algorithms to solve optimization and sequential decision-making problems in communication systems. The problems include blockchain networks, integrated sensing-communications, rate splitting multiple access, and edge computing. During my PhD studies at UTS, I became interested in advanced topics related to virtual reality, brain-computer interfaces, 3D body motion tracking, and their potential applications in future communication systems. As my research interests expanded, I began to explore new frameworks such as generative models, graphical models, and information theory tools to better understand and analyze these topics.

News

• [May 2024] Our paper “Reconstructing Human Pose from Inertial Measurements: A Generative Model-based Compressive Sensing Approach” is accepted to IEEE JSAC - Special Issue on Positioning and Sensing Over Wireless Networks (IF=16.4)
• [Apr. 2024] Our paper “A Human-Centric Metaverse Enabled by Brain-Computer Interface: A Survey” is accepted to IEEE COMST (IF=35.6)
• [Nov. 2023] Our paper “Reconstructing Human Pose from Inertial Measurements: A Generative Model-based Compressive Sensing Approach” is submitted to IEEE JSAC
• [Nov. 2023] I am elected as the Vice-Chair of the IEEE Student Branch at UTS
• [Aug. 2023] Our paper “Toward BCI-enabled Metaverse: A Joint Learning and Resource Allocation Approach” is accepted to IEEE Globecom 2023
• [Jul. 2023] Our paper “A Human-Centric Metaverse Enabled by Brain-Computer Interface: A Survey” is submitted to IEEE COMST

Awards

• [Nov. 2023] Honorary Mention, IEEE ComSoc Student Competition, “Communications Technology Changing the World”
• [Nov. 2023] Outstanding Higher Degree Research Student Award, School of Electrical and Data Engineering, UTS
• [Apr. 2023] IEEE ComSoc Student Travel Grant, ICC, Rome, Italy
• [Nov. 2021] ARC DECRA Funded Project Scholarship, University of Technology, Australia
• [Nov. 2021] UTS International Research Scholarship (UTS IRS)

Selected Publications

Services

Journal Reviewers

• IEEE Journals on Selected Areas in Communications (JSAC) 2022, 2023
• IEEE Communications Surveys and Tutorial (COMST) 2022
• IEEE Transactions on Wireless Communications (TWC) 2023
• IEEE Transactions on Communications (TCOM) 2022
• IEEE Transactions of Mobile Computing (TMC) 2023, 2024
• IEEE Transactions on Cognitive Communications and Networking (TCCN) 2023, 2024
• IEEE Transactions on Vehicular Technology (TVT) 2023, 2024
• IEEE Internet of Things Journal (IOTJ) 2021
• IEEE Wireless Communications Letters (WCL) 2021, 2022, 2024
• IEEE Wireless Communications Letters (CL) 2021
• IEEE Open Journal of the Communications Society (OJCOMST) 2023

Conference/Workshop Reviewers

• IEEE Global Communications Conference, 4–8 December 2023, Kuala Lumpur, Malaysia.
• IEEE 98th Vehicular Technology Conference: VTC2023-Fall, 10-13 October 2023, Hong Kong
• IEEE 97th Vehicular Technology Conference: VTC2023-Spring, 20-23 June 2023, Florence, Italy
• IEEE Wireless Communications and Networking Conference (WCNC), 26–29 March, 2023, Glasgow, Scotland, UK
• IEEE Wireless Communications and Networking Conference (WCNC), 10-13 April, 2022, Austin, TX, USA

Teaching

• Tutoring for IoT Security (42037), UTS, 2023

IEEE Student Brach

• Vice-Chair of the IEEE Student Branch at UTS, New South Wales, Australia, 2023

All publications

Preprints

• [P2] M. A. Hassan, M. B. Jamshidi, B. D. Manh, N. H. Chu, C. H. Nguyen, N. Q. Hieu, C. T. Nguyen, D. T. Hoang, D. N. Nguyen, N. V. Huynh, M. A. Alsheikh, and E. Dutkiewicz, "Enabling Technologies for Web 3.0: A Comprehensive Survey," [arxiv].

• [P1] N. Q. Hieu, D. T. Hoang, D. N. Nguyen, V. D. Nguyen, Y. Xiao, and E. Dutkiewicz, "Enhancing Immersion and Presence in the Metaverse with Over-the-Air Brain-Computer Interface," IEEE Transactions on Wireless Communications (major revision) [arxiv].

Journals

• [J10] N. Q. Hieu, D. T. Hoang, D. N. Nguyen, and M. A. Alsheikh, "Reconstructing Human Pose from Inertial Measurements: A Generative Model-based Compressive Sensing Approach," IEEE Journal on Selected Areas in Communications (accepted) [arxiv] [code].

• [J9] H. Y. Zhu, N. Q. Hieu, D. T. Hoang, D. N. Nguyen, and C.T. Lin, "A Human-Centric Metaverse Enabled by Brain-Computer Interface: A Survey," IEEE Communications Surveys & Tutorials (accepted) (IF=35.6, Q1) [pdf].

• [J8] N. Q. Hieu, D. N. Nguyen, D. T. Hoang, and E. Dutkiewicz, "When Virtual Reality Meets Rate Splitting Multiple Access: A Joint Communication and Computation Approach," IEEE Journal on Selected Areas in Communications, vol. 41, no. 5, pp. 1536-1548, May 2023 (IF=16.4, Q1) [arxiv] .

• [J7] N. Q. Hieu, D. T. Hoang, D. Niyato, D. N. Nguyen, D. I. Kim, and A. Jamalipour, "Joint Power Allocation and Rate Control for Rate Splitting Multiple Access Networks with Covert Communications," IEEE Transactions on Communications, vol. 71, no. 4, pp. 2274-2287, Apr. 2023 (IF=8.3, Q1) [arxiv] .

• [J6] N. Q. Hieu, D. T. Hoang, D. Niyato, P. Wang, D. In Kim, and C. Yuen, "Transferable Deep Reinforcement Learning Framework for Autonomous Vehicles with Joint Radar-Data Communications," IEEE Transactions on Communications, vol. 7, no. 8, Aug. 2022 (IF=8.3, Q1) [arxiv] .

• [J5] N. Q. Hieu, T. T. Anh, N. C. Luong, D. Niyato, D. I. Kim, and E. Elmroth, "Resource Management for Blockchain-enabled Federated Learning: A Deep Reinforcement Learning Approach," IEEE Networking Letter, vol. 4, no. 3, Sep. 2022.

• [J4] K. S. H. Ong, W. Wang, N. Q. Hieu, D. Niyato, and T. Friedrichs, "Predictive Maintenance Model for IIoT-based Manufacturing: A Transferable Deep Reinforcement Learning Approach," IEEE Internet of Things Journal, vol. 9, no. 17, Sep. 2022 (IF = 10.6, Q1).

• [J3] N. Q. Hieu, D. T. Hoang, D. Niyato, and D. In Kim, "Optimal Power Allocation for Rate Splitting Communications with Deep Reinforcement Learning," IEEE Wireless Communications Letters, vol. 10. no.12, Oct. 2021 (IF=6.3, Q1) [arxiv] .

• [J2] N. V. Tam, N. Q. Hieu, N. T. T. Van, N. C. Luong, D. Niyato, and D. I. Kim, "Adaptive Task Offloading in Coded Edge Computing: A Deep Reinforcement Learning Approach," IEEE Communications Letters, vol. 25, no. 12, Sep. 2021(IF=4.1, Q1).

• [J1] N. Q. Hieu, D. T. Hoang, N. C. Luong, and D. Niyato, "iRDRC: An Intelligent Real-Time Dual-Functional Radar-Communication System for Automotive Vehicles," IEEE Wireless Communications Letters, no. 9, vol. 12, pp.2140-2143, Aug. 2020 (IF=6.3, Q1)

Conferences

• [C5] N. Q. Hieu, D. T. Hoang, D. N. Nguyen, and E. Dutkiewicz, "Toward BCI-enabled Metaverse: A Joint Learning and Resource Allocation Approach," IEEE Global Communications Conference, December 2023, Malaysia.

• [C4] N. Q. Hieu, N. H. Chu, D. T. Hoang, D. N. Nguyen, and E. Dutkiewicz, "A Unified Resource Allocation Framework for Virtual Reality Streaming over Wireless Networks," IEEE International Conference on Communications, May 2023, Italy.

• [C3] N. V. Huynh, N. Q. Hieu, N. H. Chu, D. N. Nguyen, D. T. Hoang, and E. Dutkiewicz, "Defeating Eavesdroppers with Ambient Backscatter Communications," IEEE Wireless Communications and Networking Conference, March 2023, United Kingdom.

• [C2]N. Q. Hieu, T. T. Huong, N. T. Hung, N. Q. Thu and N. H. Thanh, "A Low-Power, High Reliable Data Collection Scheme for Wireless Sensor Networks," International Conference on Advanced Technologies for Communications (ATC), Hanoi, Vietnam, 2019, pp. 258-263.

• [C1] N. Q. Hieu, N. Huu Thanh, T. T. Huong, N. Quynh Thu and H. V. Quang, "Integrating Trickle Timing in Software Defined WSNs for Energy Efficiency," IEEE Seventh International Conference on Communications and Electronics (ICCE), Hue, Vietnam, 2018, pp. 75-80.

Favorite Reading List

I really enjoy reading text books that write about fundamental concepts in machine learning, information theory, and network information theory:

• Reinforcement Learning: An Introduction, 2nd edition, by R.S. Sutton and A. G. Barto

• Elements of Information Theory, 2nd edition, by T. M. Cover and J. A. Thomas

• Graphical models for machine learning and digital communication, by B. J. Frey

• Information theory, inference, and learning algorithms, by David J. C. MacKay