人员简介

POSITION/TITLE

Research Scientist, Shenzhen Research Institute of Big Data

Adjunct Assistant Professor, School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen

RESEARCH FIELD

Massive Random Access for Internet of Things, Deep Learning/Optimization for Wireless Communications, Distributed Signal Processing for Cell-Free Massive MIMO

EMAIL

liyang@sribd.cn or liyang@cuhk.edu.cn

EDUCATION BACKGROUND

Ph.D., Electrical and Electronic Engineering, The University of Hong Kong (HKU)

M.E., Electronic Information Engineering, Beihang University (BUAA)

B.E., Electronic Information Engineering, Beihang University (BUAA)

HONORS AND AWARDS

Shenzhen Overseas High-Level Talent, 2020

Shenzhen Dragon Talent, 2020

Innovation Pioneer Award, Huawei Technologies Co., Ltd., 2020

BIOGRAPHY

Dr. Yang Li currently works as a Research Scientist (副研究员) in Shenzhen Research Institute of Big Data, and also as an Adjunct Assistant Professor at the School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen. He obtained his Ph.D. in Electrical and Electronic Engineering from The University of Hong Kong (HKU), along with the B.E. and M.E. degrees in Electronic Information Engineering from Beihang University (BUAA). His research expertise lies at the intersection of wireless communications, deep learning, and optimization, with extensive experience and substantial contributions in developing distributed optimization and deep learning algorithms for optimization problems arising in Internet of Things (IoT), cell-free massive MIMO, and large-scale wireless networks. He has been the principal investigator of four national research projects/sub-projects. He is the first or corresponding author of more than 20 papers published in top international journals (SCI, Q1), such as IEEE Transactions on Wireless Communications and IEEE Transactions on Signal Processing. He was a recipient of the 2020 Innovation Pioneer Award from Huawei.

REPRESENTATIVE PUBLICATIONS (* denotes the corresponding author)

[1] Qingfeng Lin, Yang Li*, Yik-Chung Wu, and Rui Zhang, “Intelligent Reflecting Surface Aided Activity Detection for Massive Access: Performance Analysis and Learning Approach,” IEEE Transactions on Wireless Communications, early access, Aug. 2024.

[2] Yang Li, Ya-Feng Liu, Fan Xu, Qingjiang Shi, and Tsung-Hui Chang, “Learning to Optimize QoS-Constrained Beamforming in Multi-User Systems: A Penalty-Dual Framework,” IEEE Transactions on Wireless Communications, early access, Aug. 2024.

[3] Qingfeng Lin, Yang Li*, Wei-Bin Kou, Tsung-Hui Chang, and Yik-Chung Wu, “Communication-Efficient Activity Detection for Cell-Free Massive MIMO: An Augmented Model-Driven End-to-End Learning Framework,” IEEE Transactions on Wireless Communications, vol: 23, no. 10, pp. 12888-12903, Oct. 2024.

[4] Yang Li and Ya-Feng Liu, “HPE Transformer: Learning to Optimize Multi-Group Multicast Beamforming Under Nonconvex QoS Constraints,” IEEE Transactions on Communications, vol. 72, no. 9, pp. 5581-5594, Sep. 2024.

[5] Yunqi Wang, Yang Li*, Qingjiang Shi, and Yik-Chung Wu, “ENGNN: A General Edge-Update Empowered GNN Architecture for Radio Resource Management in Wireless Networks,” IEEE Transactions on Wireless Communications, vol. 23, no. 6, 5330-5344, Jun. 2024.

[6] Hao Zhang, Qingfeng Lin, Yang Li*, Lei Cheng, and Yik-Chung Wu, “Activity Detection for Massive Connectivity in Cell-free Networks with Unknown Large-scale Fading, Channel Statistics, Noise Variance, and Active Probability: A Bayesian Approach,” IEEE Transactions on Signal Processing, vol. 72, pp. 942-957, 2024.

[7] Yang Li, Zhilin Chen, Yunqi Wang, Chenyang Yang, Bo Ai, and Yik-Chung Wu, “Heterogeneous Transformer: A Scale Adaptable Neural Network Architecture for Device Activity Detection,” IEEE Transactions on Wireless Communications, vol. 22, no. 5, pp. 3432-3446, May 2023.

[8] Yang Li, Qingfeng Lin, Ya-Feng Liu, Bo Ai, and Yik-Chung Wu, “Asynchronous Activity Detection for Cell-Free Massive MIMO: From Centralized to Distributed Algorithms,” IEEE Transactions on Wireless Communications, vol. 22, no. 4, pp. 2477-2492, Apr. 2023.

[9] Qingfeng Lin, Yang Li*, and Yik-Chung Wu, “Sparsity Constrained Joint Activity and Data Detection for Massive Access: A Difference-of-Norms Penalty Framework,” IEEE Transactions on Wireless Communications, vol. 22, no. 3, pp. 1480-1494, Mar. 2023.  

[10] Yang Li, Minghua Xia, and Yik-Chung Wu, “Cache Allocation at Base Stations with Multi-Cluster Multicast Backhaul via Accelerated First-Order Algorithm,” IEEE Transactions on Wireless Communications, vol. 19, no. 5, pp. 2920-2933, May 2020.

[11] Yang Li, Minghua Xia, and Yik-Chung Wu, “Energy-Efficient Precoding for Non-Orthogonal Multicast and Unicast Transmission via First-Order Algorithm,” IEEE Transactions on Wireless Communications, vol. 18, no. 9, pp. 4590-4604, Sep. 2019.

[12] Yang Li, Minghua Xia, and Yik-Chung Wu, “Activity Detection for Massive Connectivity under Frequency Offsets via First-Order Algorithms,” IEEE Transactions on Wireless Communications, vol. 18, no. 3, pp. 1988-2002, Mar. 2019.

[13] Yang Li, Minghua Xia, and Yik-Chung Wu, “First-Order Algorithm for Content-Centric Sparse Multicast Beamforming in Large-Scale C-RAN,” IEEE Transactions on Wireless Communications, vol. 17, no. 9, pp. 5959-5974, Sep. 2018.

[14] Yang Li, Yafei Tian, and Chenyang Yang, “Energy-Efficient Coordinated Beamforming Under Minimal Data Rate Constraint of Each User,” IEEE Transactions on Vehicular Technology, vol. 64, no. 6, pp. 2387-2397, Jun. 2015.