16 citations · 26 across the 14 of their papers we have counts for
19 papers
Cell-Free Massive MIMO with Multi-Antenna Users and Phase Misalignments: A Novel Partially Coherent Transmission Framework
Unnikrishnan Kunnath Ganesan, Tung Thanh Vu, Erik G. Larsson
Cell-free massive multiple-input multiple-output (MIMO) is a promising technology for next-generation communication systems. This work proposes a novel partially coherent (PC) tran…
Joint User Association and Power Control for Cell-Free Massive MIMO
Chongzheng Hao, Tung Thanh Vu, Hien Quoc Ngo +4
This work proposes novel approaches that jointly design user equipment (UE) association and power control (PC) in a downlink user-centric cell-free massive multiple-input multiple-…
Network-Assisted Full-Duplex Cell-Free Massive MIMO: Spectral and Energy Efficiencies
Mohammadali Mohammadi, Tung T. Vu, Hien Quoc Ngo +1
We consider network-assisted full-duplex (NAFD) cell-free massive multiple-input multiple-output (CF-mMIMO) systems, where full-duplex (FD) transmission is virtually realized via h…
Massive MIMO for Serving Federated Learning and Non-Federated Learning Users
Muhammad Farooq, Tung Thanh Vu, Hien Quoc Ngo +1
With its privacy preservation and communication efficiency, federated learning (FL) has emerged as a promising learning framework for beyond 5G wireless networks. It is anticipated…
Serving Federated Learning and Non-Federated Learning Users: A Massive MIMO Approach
Muhammad Farooq, Tung T. Vu, Hien Quoc Ngo +1
Federated learning (FL) with its data privacy protection and communication efficiency has been considered as a promising learning framework for beyond-5G/6G systems. We consider a…
Channel Estimation in RIS-assisted Downlink Massive MIMO: A Learning-Based Approach
Tung T. Vu, Trinh Van Chien, Canh T. Dinh +2
For downlink massive multiple-input multiple-output (MIMO) operating in time-division duplex protocol, users can decode the signals effectively by only utilizing the channel statis…
Virtually Full-duplex Cell-Free Massive MIMO with Access Point Mode Assignment
Mohammadali Mohammadi, Tung T. Vu, Behnaz Naderi Beni +2
We consider a cell-free massive multiple-input multiple-output (MIMO) network utilizing a virtually full-duplex (vFD) mode, where access points (APs) with a downlink (DL) mode and…
Data Size-Aware Downlink Massive MIMO: A Session-Based Approach
Tung T. Vu, Hien Quoc Ngo, Minh N. Dao +2
This letter considers the development of transmission strategies for the downlink of massive multiple-input multiple-output networks, with the objective of minimizing the completio…
Energy-Efficient Massive MIMO for Federated Learning: Transmission Designs and Resource Allocations
Tung T. Vu, Hien Q. Ngo, Minh N. Dao +3
This work proposes novel synchronous, asynchronous, and session-based designs for energy-efficient massive multiple-input multiple-output networks to support federated learning (FL…
Energy-Efficient Massive MIMO for Serving Multiple Federated Learning Groups
Tung T. Vu, Hien Quoc Ngo, Duy T. Ngo +2
With its privacy preservation and communication efficiency, federated learning (FL) has emerged as a learning framework that suits beyond 5G and towards 6G systems. This work looks…
How Does Cell-Free Massive MIMO Support Multiple Federated Learning Groups?
Tung T. Vu, Hien Quoc Ngo, Thomas L. Marzetta +1
Federated learning (FL) has been considered as a promising learning framework for future machine learning systems due to its privacy preservation and communication efficiency. In b…
A New Look and Convergence Rate of Federated Multi-Task Learning with Laplacian Regularization
Canh T. Dinh, Tung T. Vu, Nguyen H. Tran +2
Non-Independent and Identically Distributed (non- IID) data distribution among clients is considered as the key factor that degrades the performance of federated learning (FL). Sev…
Joint Resource Allocation to Minimize Execution Time of Federated Learning in Cell-Free Massive MIMO
Tung T. Vu, Duy T. Ngo, Hien Quoc Ngo +3
Due to its communication efficiency and privacy-preserving capability, federated learning (FL) has emerged as a promising framework for machine learning in 5G-and-beyond wireless n…
Cell-Free Massive MIMO for Wireless Federated Learning
Tung T. Vu, Duy T. Ngo, Nguyen H. Tran +3
This paper proposes a novel scheme for cell-free massive multiple-input multiple-output (CFmMIMO) networks to support any federated learning (FL) framework. This scheme allows each…
Joint Optimization of User Association, Data Delivery Rate and Precoding for Cache-Enabled F-RANs
Tung T. Vu, Duy T. Ngo, Lawrence Ong +2
This paper considers the downlink of a cache-enabled fog radio access network (F-RAN) with limited fronthaul capacity, where user association (UA), data delivery rate (DDR) and sig…
Interference Alignment Designs for Secure Multiuser MIMO Systems: Rank Constrained Rank Minimization Approach
Tung T. Vu, Ha Hoang Kha, Trung Q. Duong
In this paper, we formulate the interference alignment (IA) problem for a multiuser multiple-input multiple-output (MIMO) system in the presence of an eavesdropper as a rank constr…
Particle Swarm Optimization for Weighted Sum Rate Maximization in MIMO Broadcast Channels
Tung T. Vu, Ha Hoang Kha, Trung Q. Duong +1
In this paper, we investigate the downlink multiple-input-multipleoutput (MIMO) broadcast channels in which a base transceiver station (BTS) broadcasts multiple data streams to K M…
Wiretapped Signal Leakage Minimization for Secure Multiuser MIMO Systems via Interference Alignment
Tung T. Vu, Ha Hoang Kha, Trung Q. Duong +1
In this paper, interference alignment (IA) is designed for secure multiuser multiple-input multiple-output systems in the presence of an eavesdropper. The proposed IA technique des…
On the Interference Alignment Designs for Secure Multiuser MIMO Systems
Kha Hoang Ha, Thanh Tung Vu, Trung Quang Duong +1
In this paper, we propose two secure multiuser multiple-input multiple-output transmission approaches based on interference alignment (IA) in the presence of an eavesdropper. To de…