8 papers
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…
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 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…