Xiaoxu Zhang, a Doctor of Engineering, is an Associate Professor and a Master's Supervisor. She is also an IEEE Senior Member. In June 2019, she graduated with a doctoral degree from the National Key Laboratory of Communication Anti-interference Technology at University of Electronic Science and Technology of China, majoring in Communication and Information Systems. From August 2017 to August 2018, she was a nationally-sponsored overseas student at McGill University in Canada, majoring in Electronic and Computer Engineering. Her main research fields include wireless communication, sparse signal processing, communication perception integration, high mobility communication, Bayesian learning theory, machine learning, etc. In recent years, she has published over 30 papers in international top journals and conferences such as IEEE Transactions on Wireless Communications, IEEE Transactions on Vehicular Technology, IEEE International Conference on Communications, etc. She serves as a reviewer for several international journals and conferences in the field of communication, including IEEE Transactions on Wireless Communications, IEEE Transactions on Vehicular Technology, IEEE Wireless Communications Letters, IEEE Vehicular Technology Conference, etc. She has also been the principal investigator of projects such as the National Natural Science Foundation of China's Youth Science Fund, Sichuan Provincial Natural Science Foundation's Youth Science Fund/Series Project, and has participated in projects such as the National Natural Science Foundation of China's Key International and Regional Cooperation Research Project, National Natural Science Foundation of China's Joint Fund Project, National Key Research and Development Program, and Sichuan Provincial Science and Technology Department's Key Research and Development Program.

Welcome students who are interested in wireless communication, signal processing, and machine learning research to join us!

About me

(A). Research interest:

6G, wireless communications, sparse signal processing, integrated sensing and communication, high mobility communications, machine learning, Bayesian learning theory

(B).Research Projects.

Selected projects:

[1] Key Research Project of the Ministry of Science and Technology of the People's Republic of China, Theory and Technology of Large Dimensional Random Access, 2019- 2023, Main Researcher, Completed.

[2] National Natural Science Foundation of China, Young Science Fund Project, Research on Large-scale MTC Communication Signal Detection Based on Bayesian Compressed Sensing, 2021-2023, Principal Investigator, Completed.

[3] Key International and Regional Cooperation Research Project of the National Natural Science Foundation of China, Research on Large-scale Internet of Things Multiple Access and Coding Problems, 2021 - 2025, Main Researcher, Completed

[4] Youth Science Fund of Sichuan Provincial Science and Technology Department, Theory and Technology for Large-scale Internet of Things Multi-User Detection Based on Bayesian Compressed Sensing, 2022-2024, Principal Investigator, Completed.

[5] Sichuan Provincial Natural Science Foundation of China, Research on Efficient Signal Detection Methods for 6G Large-scale Internet of Things Based on Structural Sparse Features, 2026-2027, principal investigator, ongoing.

(C).Teaching

Mobile communications (Spring 2023, 2024, 2025), 3-credit core course for Communication Engineering Students.

Introduction to the Frontiers of Communication Science (Autumn 2026), 2-credit core course for Communication Engineering Students.

(D).Supervision:

Proudly to work with following team members:

Ph.D. (Co-supervisor)

1. Yang Boyan, 2021-2025;

2. Qiu Wenduo, since 2023;

3. Liang Yuanyi, since 2025;

4. Jiang Dexia, since 2026

Master students

1. Zhou Ziyang, 2022-2024 (Outstanding Graduate, National Award)

2. Lan Xuping, 2023-2025 (National Award)

3. He Yi, 2023-2025

4. Shi Fengwen, 2024 to present

5. Qing Wanjun, 2024 to present

6. Li Yi, 2025 to present

7. Peng Wenbo, 2025 to present

8. Liu Jixin, 2026 to present

9. He Haitao, 2026 to present

Undergraduate students

1. Zong An, 2022-2023

2. Chen Qiyeng, 2023-2024

3. Zheng Dongping, 2023-2024

4. Yang Jiarun, 2023-2024

5. Lei Ruibin, 2023-2025 (Outstanding Graduation Thesis)

6. Meng Yuchao, 2023-2025

7. Zhang Zhiyuan, 2024-2025

8. Li Xiangrui, 2024-2025

9. Qin Yuhuan, 2024-2026

10. Gong Bingxin, 2025-2026

11. Fang Jiaxin, 2025-2026

12. SRTP Competition, 2025-2026, Kong Weixuan, Chen Lin, Chen Xingyi, Wu Zhongqi (Outstanding Project)

13. SRTP Competition, 2025-2026, Wang Junjie, Si Tianrui, Yang Ruirui, Wang Penglai, Jiang Xinrui

(E). Selected Recent Publication:

Journal Articles

[1] Xiaoxu Zhang*; Fabrice Labeau; Li Hao; Jiaqi Liu, Joint active user detection and channel estimation via Bayesian learning approaches in MTC communications, IEEE Transactions on Vehicular Technology, 2021, 70(6): 6222-6226.

[2] Jiaqi Liu; Gang Wu*; Xiaoxu Zhang; Shu Fang; Shaoqian Li, Modeling, analysis, and optimization of Grant-Free NOMA in massive MTC via stochastic geometry, IEEE Internet of Things Journal, 2021, 8(6): 4389-4402. (outstanding paper)

[3] Xiaoxu Zhang*; Pingzhi Fan; Jiaqi Liu; Li Hao, Bayesian learning based multiuser detection for grant-free NOMA systems, IEEE Transactions on Wireless Communications, 2022, 21(8): 6317-6328.

[4] Xiaoxu Zhang*; Pingzhi Fan; Li Hao; Xin Quan, Generalized Approximate Message Passing Based Bayesian Learning Detectors for Uplink Grant-Free NOMA, IEEE Transactions on Vehicular Technology, 2023, 72(11): 15057-15061.

[5] Boran Yang, Xiaoxu Zhang*, Li Hao, and George K. Karagiannidis, Improved Bayesian Learning Detectors for Uplink Grant-Free MIMO-NOMA, IEEE Wireless Communications Letters, 2023, 12(12): 2243-2247.

[6] Xiaoxu Zhang*, Pingzhi Fan, Li Li, Li Hao, and Ziyang Zhou, Structured Sparse Bayesian Learning Based Multiuser Detectors for Uplink Grant-Free NOMA with Variable User Activities, IEEE Transactions on Vehicular Technology, 2024, 73(6): 9093-9097.

[7] Xiaoxu Zhang*, Ziyang Zhou, Zhiguo Ding, Zheng Ma, and Li Hao, Joint Sparse Channel Estimation and Multiuser Detection Using Spike and Slab Prior-Based Gibbs Sampling for Uplink Grant-Free NOMA, IEEE Transactions on Vehicular Technology, 2024, 73(12): 19338-19349.

[8] Xiaoxu Zhang*, Ziyang Zhou, Li Zhang, Pingzhi Fan, and Zheng Ma, Multiuser Detection with Compressive Sensing Iterative Reweighed Approach for Grant-Free MIMO-NOMA Systems, IEEE Transactions on Vehicular Technology, 2025, 74(1):1742-1746.

[9] Ruibin Lei, Xiaoxu Zhang*, Fengwen Shi, Xiangwei Zhou, Zhengchun Zhou, and Jiaqi Liu, Block Iterative Support Detection for Uplink Grant-Free MIMO-NOMA, IEEE Wireless Communications Letters, 2025, 14(4): 1264-1268.

[10] Boran Yang, Xiaoxu Zhang*, Li Hao, and George K. Karagiannidis, Joint Activity Detection and Channel Estimation in MIMO Grant-Free Random Access Networks, IEEE Transactions on Wireless Communications, 2025, 24(6): 4793–4808.

[11] Xiaoxu Zhang*; Yuchao Meng; George K. Karagiannidis; Zheng Ma; Gang Liu; Boran Yang, Channel Estimation with Iterative Hard Thresholding in mMTC Communications, IEEE Transactions on Vehicular Technology, 2026, 75(6): 11687-11691.

Conference Papers

[1] Xiaoxu Zhang; Li Hao; Pingzhi Fan; Jiaqi Liu; Linxiao Yang, Iterative reweighed approach for multiuser detection with multiple measurement vector in MTC communications, IEEE Vehicular Technology Conference, Antwerp, Belgium, 2020.

[2] Xiaoxu Zhang; Pingzhi Fan; Li Hao; Jiaqi Liu, Two efficient Bayesian multiuser detection algorithms for machine-type communications, IEEE Vehicular Technology Conference, Norman, OK, USA, 2021.

[3] Boran Yang, Xiaoxu Zhang, Li Hao, George K. Karagiannidis, and Xin Quan, Cost-Efficient VBI-Based Multiuser Detection for Uplink Grant-Free MIMO-NOMA, IEEE Vehicular Technology Conference, Singapore, 2024.

[4] Boran Yang, Xiaoxu Zhang, Li Hao, George K. Karagiannidis, and Pingzhi Fan, Joint Activity Detection and Channel Estimation for MIMO Grant-Free Random Access through Bayesian Learning, IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, Valencia, Spain, 2024.

[5] Wenduo Qiu, Xiaoxu Zhang, George K. Karagiannidis, Li Hao, Ming Xiao, Xueping Lan, Student-T Prior Sparse Bayesian Learning for Improved Channel Estimation in OTFS Systems, IEEE Vehicular Technology Conference, Washington DC, USA, 2024.

[6] Xueping Lan, Xiaoxu Zhang*, Pingzhi Fan, Zhengquan Zhang, Yi Zhou, Li Hao, Zheng Ma, Efficient Signal Detection Method Based on Sparse Bayesian Learning in ZP-OTFS Systems, 11th international workshop on signal design and its applications in communications (IWSDA 2025), Melbourne, Australia.

[7] Xueping Lan, Xiaoxu Zhang, George K. Karagiannidis, Ming Xiao, Jingfu Li, and Zheng Ma, Low-Complexity Bayesian Learning with Adaptive Matrix Optimization for OTFS Channel Estimation, IEEE Vehicular Technology Conference, Nice, France, 2026.

(F). Selected Recent Patents:

[1] Xiaoxu Zhang, Ziyang Zhou, Boran Yang, Li Hao, Xin Quan, A time-dependent sparse signal recovery method, 2023

[2] Boran Yang, Xiaoxu Zhang, Li Hao, Ziyang Zhou, Xin Quan, A license-free joint active user and data detection method, 2024

[3] Xiaoxu Zhang, Xueping Lan, Ziyang Zhou, Xin Quan, A sparse Bayesian signal reconstruction method based on multiple measurement vector model, 2024

[4] Xiaoxu Zhang, Yi He, Boran Yang, Li Hao, A block sparse Bayesian multi-slot data detection method, 2025

[5] Xiaoxu Zhang, Xueping Lan, Pingzhi Fan, Fengwen Shi, Zheng Ma, Li Hao, An efficient OTFS sparse channel estimation method based on fast sparse Bayes, 2025

[6] Xiaoxu Zhang, Xueping Lan, Wenduo Qiu, Wanjun Qing, Li Hao, Zheng Ma, An OTFS sparse channel estimation method based on unitary transform and sparse Bayes, 2025

(H). Others

• IEEE Senior Member;

•   Reviewer: IEEE TWC, TCOM, TVT, WCL, CL, VTC, ICC, etc

• Track Chair/ Co-chair: IEEE ISWCS 2026, JCICE 2026, ICTC 2026, ICCCS 2026

• Conference TPC Member: IEEE WCSP 2020/2023/2024