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Dr Yixuan Zou

Yixuan

Lecturer in Digital Signal Processing

Email: yixuan.zou@qmul.ac.uk
Room Number: Engineering, Eng 212
Website: http://www.eecs.qmul.ac.uk/~yz323/

Profile

Dr. Yixuan Zou is a Lecturer in Digital Signal Processing at Queen Mary University of London (QMUL). She also teaches on the Joint Programme (JP) between QMUL and Beijing University of Posts and Telecommunications (BUPT).

She received the B.Sc. degree in Mathematics and the M.Sc. degree from Imperial College London, U.K., in 2017 and 2018, respectively. In 2022, she received her Ph.D. degree in Computer Science, Queen Mary University of London. Her research interests include artificial intelligence (AI) for wireless communications, non-orthogonal multiple access (NOMA), IRSs/RISs aided communications, and resource allocation for 6G networks.

She is an academic Fellow at the Digital Environment Research Institute (DERI). She served as a Technical Program Committee member for IEEE VTC2023-Fall and VTC2024-Fall; the session chairs for a workshop and various symposiums at IEEE ICC 2023 and Globecom 2023; and the Local Management Officer of NGMA-ETI 1st & 2nd QMUL 6G Workshop.

Teaching

2024-2025

BBC6501 Deputy Final Year Project Coordinator

CBU5201 Machine Learning

EBU5376 Digital Signal Processing

 

2023-2024

BBC6501 Final Year Project Co-coordinator

CBU5201 Machine Learning

EBU5376 Digital Signal Processing

EBU6018 Advanced Transform Methods 

 

2022 - 2023

EBU5376 Digital Signal Processing

EBU6018 Advanced Transform Methods

EBU4001 Personal Development Plan (PDP) 

Research

Research Interests:

  • Meta Learning
  • Deep Learning
  • Deep Reinforcement Learning
  • Non-Orthogonal Multiple Access
  • Reconfigurable Intelligent Surface

Publications

Full list of publications

Journal Articles (in Print/Press)

J4. J. Zuo, Y. Liu, C. Zhu, Y. Zou, D. Zhang and N. Al-Dhahir, "Exploiting NOMA and RIS in Integrated Sensing and Communication," IEEE Transactions on Vehicular Technology, vol. 72, no. 10, pp. 12941-12955, Oct. 2023
J3. Y. Zou, Y. Liu, X. Liu, X. Mu, X. Zhang, C. Yuen, “Machine Learning in RIS-assisted NOMA IoT Networks”, IEEE Internet of Things Journal, vol. 10, no. 22, pp. 19427-19440, Nov. 2023.
J2. Y. Xu, T. Zhang, Y. Zou, Y. Liu, “Reconfigurable Intelligence Surface Aided UAV-MEC Systems With NOMA”, IEEE Communication Letters, vol. 26, no. 9, pp. 2121-2125, Sept. 2022.
J1. L. Guo, J. Jia, Y. Zou, Y. Liu, J. Chen, X. Wang, “Resource Allocation for Multiple RISs Assisted NOMA Empowered D2D Communication: A MAMP-DQN Approach”, Ad Hoc Networks, vol. 146, Jul. 2023. 

Journal Articles (in Submission)

1. J. Chen, Z. Ma, Y. Zou, Y. Liu, J. Jia, X. Wang, “Joint Active and Passive Beamforming for EE Optimization in STAR-RIS assisted CoMP Systems”, IEEE Transactions on Wireless Communications; under revision.

Conference Proceedings (in Print/Press)

C8. Z. Wang, X. Mu, Y. Zou, and Y. Liu, "Near-Field Wideband Beamforming Design with Short-Range True-Time Delayers", in Proc. IEEE Int. Communications Conf. (ICC’24), Denver, CO, USA, June 2024.
C7. Z. Wang, X. Mu, Y. Zou, and Y. Liu, "Near-Field Wideband Beamfocusing Optimization: A Heuristic Two-Stage Approach", in Proc. IEEE Global Communications Conf. (GLOBECOM'23), Kuala Lumpur, Malaysia, December 2023.
C6. Z. Wang, X. Mu, J. Xu, Y. Zou, and Y. Liu, "STARS for Spectral Efficiency in Wideband Terahertz Communications", in Proc. IEEE Global Communications Conf. (GLOBECOM'23), Kuala Lumpur, Malaysia, December 2023.
C5. Y. Zou, W. Yi, X. Xu, and Y. Liu, “Adaptive NGMA Scheme for Energy-limited Networks: A Deep Reinforcement Learning Approach”, in Proc. IEEE Int. Communications Conf. (ICC’23), Rome, Italy, June 2022. 
C4. X. Gao, Y. Zou, W. Yi, J. Xu, R. Liu and Y. Liu, "Multi-objective Optimization of Energy and Latency in URLLC-enabled Wireless VR Networks," 2022 International Symposium on Wireless Communication Systems (ISWCS'22), Hangzhou, China, 2022, pp. 1-6.
C3. J. Chen, Z. Ma, Y. Zou, J. Jia, X. Wang, “DRL-based Energy Efficient Resource Allocation for STAR-RIS Assisted Coordinated Multi-cell Networks”, in Proc. IEEE Global Communications Conf. (GLOBECOM’22), Rio de Janeiro, Brazil, December 2022. 
C2. Y. Zou, Y. Liu, K. Han, X. Liu, and K. K. Chai, “Meta-learning for RIS-assisted Non-Orthogonal Multiple Access Networks”, in Proc. IEEE Global Communications Conf. (GLOBECOM’21), Madrid, Spain, December 2021. 
C1. Y. Zou, Z. Qin and Y. Liu, “Joint User Activity and Data Detection in Grant-Free NOMA using Generative Neural Networks,” in Proc. IEEE Int. Communications Conf. (ICC’21), Montreal, Canada, June 2021. 

Supervision

PhD students at QMUL (Second Supervisor)
  • Mr. Meng Zhang, working on Next Generation Multiple Access, Sept. 2022 – present
  • Mr. Hsienchih Ting, working on AI in near field communication, Sept. 2023 - present
  • Mr. Hao Jiang, working on Near-Field Communications, Sept. 2023 - present

PhD students at QMUL (Independent Supervisor)

  • Mr. Gao Qian, working on Human Action Recognition, Sept. 2022 – present

Public Engagement

TPC Member

  • Machine Learning for Communications, IEEE VTC 2024-Fall
  • Machine Learning and AI for Communications, IEEE VTC 2023-Fall

Session Chair

  • Next Generation Multiple Access (NGMA) for Future Wireless Communications Workshop, IEEE Globecom, 2023
  • Cognitive Radio and AI-Enabled Network Symposium, IEEE Globecom, 2023
  • Signal Processing for Communications Symposium, IEEE Globecom, 2023
  • IoT and Sensor Networks Symposium, IEEE ICC, 2023

Regular Reviewer

  • IEEE Internet of Things Journal (IoT-J)
  • IEEE Transactions on Wireless Communications (TWC)
  • IEEE Journal of Selected Topics in Signal Processing (IEEE J-STSP)
  • IEEE Wireless Communications Letters (WCL)
  • Top International Conferences on Communications: IEEE GlobeCom, IEEE ICC, IEEE VTC
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