167 citations · 216 across the 10 of their papers we have counts for
10 papers
Network Digital Twin for 6G and Beyond: An End-to-End View Across Multi-Domain Network Ecosystems
Dinh-Hieu Tran, Nazar Waheed, Yuris Mulya Saputra +12
With the rapid development of technology, the number of smart mobile users is increasing, accompanied by growing demands from applications such as virtual/augmented reality (VR/XR)…
Emerging Technologies for 6G Non-Terrestrial-Networks: From Academia to Industrial Applications
Cong T. Nguyen, Yuris Mulya Saputra, Nguyen Van Huynh +7
Terrestrial networks form the fundamental infrastructure of modern communication systems, serving more than 4 billion users globally. However, terrestrial networks are facing a wid…
Federated Learning Framework with Straggling Mitigation and Privacy-Awareness for AI-based Mobile Application Services
Yuris Mulya Saputra, Diep N. Nguyen, Dinh Thai Hoang +3
In this work, we propose a novel framework to address straggling and privacy issues for federated learning (FL)-based mobile application services, taking into account limited compu…
Transfer Learning for Future Wireless Networks: A Comprehensive Survey
Cong T. Nguyen, Nguyen Van Huynh, Nam H. Chu +7
With outstanding features, Machine Learning (ML) has been the backbone of numerous applications in wireless networks. However, the conventional ML approaches have been facing many…
Dynamic Federated Learning-Based Economic Framework for Internet-of-Vehicles
Yuris Mulya Saputra, Dinh Thai Hoang, Diep N. Nguyen +3
Federated learning (FL) can empower Internet-of-Vehicles (IoV) networks by leveraging smart vehicles (SVs) to participate in the learning process with minimum data exchanges and pr…
Enabling and Emerging Technologies for Social Distancing: A Comprehensive Survey and Open Problems
Cong T. Nguyen, Yuris Mulya Saputra, Nguyen Van Huynh +9
Social distancing plays a pivotal role in preventing the spread of viral diseases illnesses such as COVID-19. By minimizing the close physical contact among people, we can reduce t…
Federated Learning Meets Contract Theory: Energy-Efficient Framework for Electric Vehicle Networks
Yuris Mulya Saputra, Diep N. Nguyen, Dinh Thai Hoang +3
In this paper, we propose a novel energy-efficient framework for an electric vehicle (EV) network using a contract theoretic-based economic model to maximize the profits of chargin…
Energy Demand Prediction with Federated Learning for Electric Vehicle Networks
Yuris Mulya Saputra, Dinh Thai Hoang, Diep N. Nguyen +3
In this paper, we propose novel approaches using state-of-the-art machine learning techniques, aiming at predicting energy demand for electric vehicle (EV) networks. These methods…
Distributed Deep Learning at the Edge: A Novel Proactive and Cooperative Caching Framework for Mobile Edge Networks
Yuris Mulya Saputra, Dinh Thai Hoang, Diep N. Nguyen +3
This letter proposes two novel proactive cooperative caching approaches using deep learning (DL) to predict users' content demand in a mobile edge caching network. In the first app…
A Novel Mobile Edge Network Architecture with Joint Caching-Delivering and Horizontal Cooperation
Yuris Mulya Saputra, Dinh Thai Hoang, Diep N. Nguyen +1
Mobile edge caching/computing has been emerging as a promising paradigm to provide new services (e.g., ultra-high rate, ultra-reliable, and/or low-latency communications) in future…