Thanh Tung Vu

Data Scientist/Research Fellow with a PhD in Electrical Engineering, specializing in Applied Optimisation and Machine Learning.

Over the years, I have published my work on the intersection of data science and wireless communications in high-impact peer-reviewed journals, international conference proceedings, and book chapters.

A full list of papers and citations can be found on my Google Scholar.

Data Science for Wireless Communications

  1. C. T. Dinh, T. T. Vu, N. H. Tran, “Personalized Federated Learning: Theory and Open Problems”, Chapter 7, Federated Learning: Theory and Practice, Elsevier, 2023. Link
  2. C. Hao, T. T. Vu, H. Q. Ngo, M. N. Dao, X. Dang, C. Wang, M. Matthaiou, “Joint User Association and Power Control for Cell-Free Massive MIMO”, IEEE Internets of Things Journal (Impact Factor: 10.6), 2024. Link
  3. C. T. Dinh, T. T. Vu, N. H. Tran, M. N. Dao, H. Zhang, “A New Look and Convergence Rate of Federated Multi-Task Learning with Laplacian Regularization”, accepted to appear in IEEE Transactions on Neural Networks and Learning Systems (Impact Factor: 10.4), 2022. Link
  4. T. T. Vu, T. V. Chien, C. T. Dinh, H. Q Ngo, M. Matthaiou, “Channel Estimation in RIS-assisted Downlink Massive MIMO: A Learning-Based Approach”, in Proc. IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Oulu, Finland, Jul. 2022, (Invited Paper). Link

Wireless Communications for Data Science

  1. M. Farooq, T. T. Vu, Hien Q. Ngo, Le-Nam Tran, “Massive MIMO for Serving Federated Learning and Non-Federated Learning Users”, IEEE Transactions on Wireless Communications (Impact Factor: 10.4), 2023. Link
  2. T. T. Vu, H. Q. Ngo, M. N. Dao, D. T. Ngo, E. G. Larsson, T. Le-Ngoc, “Energy-Efficient Massive MIMO for Federated Learning: Transmission Designs and Resource Allocations”, IEEE Open Journal of the Communications Society (Impact Factor: 7.9), vol. 3, pp. 2329-2346, Nov. 2022. Link
  3. T. T. Vu, Duy T. Ngo, Nguyen H. Tran, Hien Quoc Ngo, Minh N. Dao, and Richard H. Middleton, “Joint Resource Allocation to Minimize Execution Time of Federated Learning in Cell-Free Massive MIMO”, IEEE Internets of Things Journal (Impact Factor: 10.6), vol. 9, no. 21, pp. 21736-21750, Nov. 2022. Link
  4. T. T. Vu, Duy T. Ngo, Nguyen H. Tran, Hien Quoc Ngo, Minh N. Dao, and Richard H. Middleton, “Cell-Free Massive MIMO for Wireless Federated Learning”, IEEE Transactions on Wireless Communications (Impact Factor: 10.4), vol. 19, no. 10, pp. 6377-6392, Oct. 2020. Link (Top 50 popular papers in Oct, Nov, Dec. 2020)

Resource Optimization in 6G Networks

  1. U. K. Ganesan, T. T. Vu, E. G. Larsson, “Cell-Free Massive MIMO with Phase Misalignments and Multi-Antenna Users: A Novel Partially Coherent Transmission Framework”, IEEE Open Journal of the Communications Society (Impact Factor: 7.9), 2024. Link
  2. M. Mohammadi, T. T. Vu, H. Q. Ngo, and M. Matthaiou, “Network-Assisted Full-Duplex Cell-Free Massive MIMO: Spectral and Energy Efficiencies”, IEEE Journal on Selected Areas in Communications (Impact Factor: 16.4), 2023. Link
  3. T. T. Vu, H. Q. Ngo, M. N. Dao, M. Matthaiou, E. G. Larsson, “Data Size-Aware Downlink Massive MIMO: A Session-Based Approach”, IEEE Wireless Communications Letter (Impact Factor: 6.3), vol. 11, no. 7, pp. 1468-1472, Jul. 2022. Link
  4. T. T. Vu, D. T. Ngo, M. N. Dao, S. Durrani, D. H. N. Nguyen and R. H. Middleton, “Energy Efficiency Maximization for Downlink Cloud Radio Access Networks With Data Sharing and Data Compression,” IEEE Transactions on Wireless Communications (Impact Factor: 10.4), vol. 17, no. 8, pp. 4955-4970, Aug. 2018. Link
  5. T. T. Vu, D. T. Ngo, M. N. Dao, S. Durrani and R. H. Middleton, “Spectral and Energy Efficiency Maximization for Content-Centric C-RANs with Edge Caching,” IEEE Transactions on Communications (Impact Factor: 8.3), vol. 66, no. 12, pp. 6628–6642, Dec. 2018. Link