◆ Theoretical Research Areas

Stochastic Optimization, Analysis and Design of Stochastic Algorithms Mathematical Core Massive MIMO Channel Estimation, Feedback, Beamforming Mission-Critical IoT, Remote State Estimation, Multi-Agent Control Federated Learning, Model-Assisted ML, Integrated AI & 6G Bayesian Signal Processing, Bayesian Model Compression,

Core Theoretical Foundations — Selected Papers

  1. Y. Yuan, D.H.K. Tsang, V.K.N. Lau, “Step Size Adaptation for Accelerated Stochastic Momentum Algorithm Using SDE Modeling and Lyapunov Drift Minimization,” IEEE Trans. Signal Processing, 2025.
  2. L. Su, V.K.N. Lau, “Accelerated Federated Learning Over Wireless Fading Channels with Adaptive Stochastic Momentum,” IEEE Internet of Things Journal, 2023.
  3. W. Zhang, B. Zhang, D. Yuan, S. Xu, V.K.N. Lau, “Distributed Online Stochastic Convex-Concave Optimization: Dynamic Regret Analyses,” IEEE Trans. Signal Processing, 2026.
  4. A. Liu, V.K.N. Lau, B. Kananian, “Stochastic Successive Convex Approximation for Non-Convex Constrained Stochastic Optimization,” IEEE Trans. Signal Processing, 2019.
  5. W. Xu, A. Liu, Y. Zhang, V. Lau, “Bayesian Deep Learning via Expectation Maximization and Turbo Deep Approximate Message Passing,” IEEE Trans. Signal Processing, 2024.

Massive MIMO — Channel Estimation, Feedback, Beamforming

  1. N.K. Jha, H. Guo, V.K.N. Lau, “Reducing CSIR Sounding Overhead in MIMO-OFDM via Bayesian End-to-End Learning with Delay-Domain Sparse Precoding,” IEEE TSP, 2026.
  2. H. Guo, J. Rao, A.M.H. Wong, R. Murch, V.K.N. Lau, “Channel Estimation and Passive Beamforming for Pixel-Based RIS with Non-Separable State Response,” IEEE TWC, 2026.
  3. J. Zhuang, H. Hou, M. Tang, W. Wang, S. Jin, V.K.N. Lau, “DMRS-Based Uplink Channel Estimation for MU-MIMO Systems with Location-Specific SCSI Acquisition,” IEEE TCOM, 2026.
  4. Y. Zhang, H. Guo, V.K.N. Lau, “A Novel Pilot Scheme for Uplink Channel Estimation for Sub-Array ELAA in XL-MIMO Systems,” IEEE TSP, 2026.
  5. X. Zheng, V.K.N. Lau, “Online Deep Neural Networks for mmWave Massive MIMO Channel Estimation With Arbitrary Array Geometry,” IEEE TSP, 2021.
  6. A. Liu, F. Zhu, V.K.N. Lau, “Closed-Loop Autonomous Pilot and Compressive CSIT Feedback Resource Adaptation in Multi-User FDD Massive MIMO Systems,” IEEE Trans. Signal Processing, 2016.
  7. J. Dai, A. Liu, V.K.N. Lau, “FDD Massive MIMO Channel Estimation with Arbitrary 2D-Array Geometry,” IEEE Trans. Signal Processing, 2018.
  8. A. Liu, V.K.N. Lau, “Phase-Only RF Precoding for Massive MIMO Systems with Limited RF Chains,” IEEE Trans. Signal Processing, 2016.
  9. A. Liu, V.K.N. Lau, “Two-Tier Precoding for FDD Multi-Cell Massive MIMO Time-Varying Interference Networks,” IEEE Trans. Wireless Communications, 2015.

Mission-Critical IoT — Remote State Estimation, Multi-Agent Control

  1. M. Tang, S. Cai, V.K.N. Lau, “Temperature Control for Cyber-Physical Thermal Systems over Wireless Networks: A Model-Assisted DRL Approach,” IEEE TSP, 2026.
  2. M. Tang, V.K.N. Lau, “Online Non-Cooperative Zero-Sum Games for Linear Systems over Wireless MIMO Fading Channels,” IEEE TCNS, 2025.
  3. M. Tang, S. Cai, V.K.N. Lau, “Online System Identification and Control for Linear Systems with Multiagent Controllers,” IEEE TAC, 2022.
  4. S. Cai, V.K.N. Lau, “Online Optimal State Feedback Control of Linear Systems over Wireless MIMO Fading Channels,” IEEE TAC, 2022.
  5. S. Cai, V.K.N. Lau, “Remote State Estimation of Nonlinear Systems Over Fading Channels via Recurrent Neural Networks,” IEEE TNNLS, 2021.
  6. M. Tang, S. Cai, V.K.N. Lau, “Remote State Estimation With Asynchronous Mission-Critical IoT Sensors,” IEEE JSAC, 2020.
  7. V.K.N. Lau, S. Cai, M. Yu, “Decentralized State-Driven Multiple Access and Information Fusion of Mission-Critical IoT Sensors for 5G Wireless Networks,” IEEE JSAC, 2020.
  8. M. Yu, S. Cai, V.K.N. Lau, “Event-Driven Sensor Scheduling for Mission-Critical Control Applications,” IEEE TSP, 2019.
  9. S. Cai, V.K.N. Lau, “Zero MAC Latency Sensor Networking for Cyber-Physical Systems,” IEEE TSP, 2018.
  10. S. Cai, V.K.N. Lau, “Modulation-Free M2M Communications for Mission-Critical Applications,” IEEE TSIPN, 2017.

Federated Learning — Model-Assisted ML, Integrated AI & 6G

  1. Z. Dong, X. Zhu, J. Cao, C.K. Tham, Z. Yang, V.K.N. Lau, “Federated Learning Over Device-Centric Cell-Free Networks: A Long-Term Perspective,” IEEE TWC, 2025.
  2. Y. Yuan, D.H.K. Tsang, V.K.N. Lau, “Combining Conjugate Gradient and Momentum for Unconstrained Stochastic Optimization with Applications to ML,” IEEE IoTJ, 2024.
  3. L. Su, V.K.N. Lau, “Accelerated Federated Learning Over Wireless Fading Channels with Adaptive Stochastic Momentum,” IEEE IoTJ, 2023.
  4. H. Ma, H. Guo, V.K.N. Lau, “Communication-Efficient Federated Multitask Learning Over Wireless Networks,” IEEE IoTJ, 2022.
  5. Y. Li, Y. Cui, V.K.N. Lau, “An Optimization Framework for Federated Edge Learning,” IEEE TWC, 2022.
  6. L. Su, V.K.N. Lau, “Decentralized Sensor Scheduling, Bandwidth Allocation, and Dynamic Quantization for FL Under Hybrid Data Partitioning,” IEEE IoTJ, 2022.
  7. F. Wang, V.K.N. Lau, “Multi-Level Over-the-Air Aggregation of Mobile Edge Computing Over D2D Wireless Networks,” IEEE TWC, 2022.
  8. Y. Xue, L. Su, V.K.N. Lau, “FedOComp: Two-Timescale Online Gradient Compression for Over-the-Air Federated Learning,” IEEE IoTJ, 2022.
  9. H. Guo, Y. Zhu, H. Ma, V.K.N. Lau, K. Huang, X. Li, H. Nong, M. Zhou, “Over-the-Air Aggregation for Federated Learning: Waveform Superposition and Prototype Validation,” J. Commun. Inf. Netw., 2021.
  10. S.M. Shah, V.K.N. Lau, “Model Compression for Communication Efficient Federated Learning,” IEEE TNNLS, 2021.
  11. F. Han, V.K.N. Lau, Y. Gong, “Over-the-Air Computation of Large-Scale Nomographic Functions in MapReduce Over the Edge Cloud Network,” IEEE IoTJ, 2021.
  12. L. Su, V.K.N. Lau, “Data and Channel-Adaptive Sensor Scheduling for Federated Edge Learning via Over-the-Air Gradient Aggregation,” IEEE IoTJ, 2021.
  13. H. Guo, A. Liu, V.K.N. Lau, “Analog Gradient Aggregation for Federated Learning Over Wireless Networks: Customized Design and Convergence Analysis,” IEEE IoTJ, 2020.
  14. B. Zhou, V.K.N. Lau, X. Wang, “Machine-Learning-Based Leakage-Event Identification for Smart Water Supply Systems,” IEEE IoTJ, 2019.
  15. C. Xiang, S. Zhang, S. Xu, X. Chen, S. Cao, G.C. Alexandropoulos, V.K.N. Lau, “Robust Sub-Meter Level Indoor Localization With a Single WiFi Access Point—Regression Versus Classification,” IEEE Access, 2019.

Bayesian Signal Processing — Model Compression, Bayesian ML

  1. Y. Gao, D.H.K. Tsang, V.K.N. Lau, “Bayesian End-to-End Learning for FDD-Massive MIMO Physical-Layer Design,” IEEE TSP, 2026.
  2. S. Wang, H. Guo, X. Zhu, C. Yin, V.K.N. Lau, “Communication-Efficient Distributed Bayesian Federated Learning Over Arbitrary Graphs,” IEEE TSP, 2025.
  3. Y. Bi, V.K.N. Lau, D.H.K. Tsang, “Model-Driven Bayesian Reinforcement Learning for IRS-Assisted Massive MIMO-OFDM Channel Feedback, Beamforming, and IRS Control,” IEEE TWC, 2025.
  4. W. Xu, A. Liu, Y. Zhang, V. Lau, “Bayesian Deep Learning via Expectation Maximization and Turbo Deep Approximate Message Passing,” IEEE TSP, 2024.
  5. H. Guo, V.K.N. Lau, “Bayesian Hierarchical Sparse Autoencoder for Massive MIMO CSI Feedback,” IEEE TSP, 2024.
  6. C. Xia, H. Guo, H. Ma, D.H.K. Tsang, V.K.N. Lau, “Multi-Resolution Model Compression for DNNs: A Variational Bayesian Approach,” IEEE TSP, 2024.
  7. C. Xia, D.H.K. Tsang, V.K.N. Lau, “Structured Bayesian Compression for DNNs Based on the Turbo-VBI Approach,” IEEE TSP, 2023.
  8. C. Xia, D.H.K. Tsang, V.K.N. Lau, “Structured Bayesian Federated Learning for Green AI: A Decentralized Model Compression Using Turbo-VBI-Based Approach,” IEEE IoTJ, 2023.
  9. Y. Zhu, H. Guo, V.K.N. Lau, “Bayesian Channel Estimation in Multi-User Massive MIMO With Extremely Large Antenna Array,” IEEE TSP, 2021.