612 citations · 2.7k across the 63 of their papers we have counts for
66 papers
Phase-Aware Localization in Pinching Antenna Systems: CRLB Analysis and ML Estimation
Hao Feng, Ebrahim Bedeer, Ming Zeng +3
Pinching antenna systems (PASS) have emerged as a promising architecture for high-frequency wireless communications. In this letter, we investigate user localization in PASS by joi…
Agentic Design Patterns: A System-Theoretic Framework
Minh-Dung Dao, Quy Minh Le, Hoang Thanh Lam +4
With the development of foundation model (FM), agentic AI systems are getting more attention, yet their inherent issues like hallucination and poor reasoning, coupled with the freq…
Efficient STAR-RIS Mode for Energy Minimization in WPT-FL Networks with NOMA
MohammadHossien Alishahi, Ming Zeng, Paul Fortier +5
With the massive deployment of IoT devices in 6G networks, several critical challenges have emerged, such as large communication overhead, coverage limitations, and limited battery…
A Coopetitive-Compatible Data Generation Framework for Cross-silo Federated Learning
Thanh Linh Nguyen, Quoc-Viet Pham
Cross-silo federated learning (CFL) enables organizations (e.g., hospitals or banks) to collaboratively train artificial intelligence (AI) models while preserving data privacy by k…
Diffusion Models for Future Networks and Communications: A Comprehensive Survey
Nguyen Cong Luong, Nguyen Duc Hai, Duc Van Le +9
The rise of Generative AI (GenAI) in recent years has catalyzed transformative advances in wireless communications and networks. Among the members of the GenAI family, Diffusion Mo…
Integration of TinyML and LargeML: A Survey of 6G and Beyond
Thai-Hoc Vu, Ngo Hoang Tu, Thien Huynh-The +4
The evolution from fifth-generation (5G) to sixth-generation (6G) networks is driving an unprecedented demand for advanced machine learning (ML) solutions. Deep learning has alread…
Recent Advances in Near-Field Beam Training and Channel Estimation for XL-MIMO Systems
Ming Zeng, Ji Wang, Wanming Hao +3
Extremely large-scale multiple-input multiple-output (XL-MIMO) is a key technology for next-generation wireless communication systems. By deploying significantly more antennas than…
"Security for Everyone" in Finite Blocklength IRS-aided Systems With Perfect and Imperfect CSI
Monir Abughalwa, Diep N. Nguyen, Dinh Thai Hoang +4
Provisioning secrecy for all users, given the heterogeneity in their channel conditions, locations, and the unknown location of the attacker/eavesdropper, is challenging and not al…
Carpe Diem: Critical Learning Period-Aware Contract-Based Incentives for Federated Learning
Thanh Linh Nguyen, Dinh Thai Hoang, Diep N. Nguyen +1
Critical learning periods (CLPs) in federated learning (FL) refer to early stages during which low-quality contributions (e.g., sparse training data availability) can permanently i…
Privacy-Preserving Cyberattack Detection in Blockchain-Based IoT Systems Using AI and Homomorphic Encryption
Bui Duc Manh, Chi-Hieu Nguyen, Dinh Thai Hoang +3
This work proposes a novel privacy-preserving cyberattack detection framework for blockchain-based Internet-of-Things (IoT) systems. In our approach, artificial intelligence (AI)-d…
Dynamic Spectrum Access for Ambient Backscatter Communication-assisted D2D Systems with Quantum Reinforcement Learning
Nguyen Van Huynh, Bolun Zhang, Dinh-Hieu Tran +5
Spectrum access is an essential problem in device-to-device (D2D) communications. However, with the recent growth in the number of mobile devices, the wireless spectrum is becoming…
A Survey on Intelligent Internet of Things: Applications, Security, Privacy, and Future Directions
Ons Aouedi, Thai-Hoc Vu, Alessio Sacco +4
The rapid advances in the Internet of Things (IoT) have promoted a revolution in communication technology and offered various customer services. Artificial intelligence (AI) techni…
Applications of Generative AI (GAI) for Mobile and Wireless Networking: A Survey
Thai-Hoc Vu, Senthil Kumar Jagatheesaperumal, Minh-Duong Nguyen +3
The success of Artificial Intelligence (AI) in multiple disciplines and vertical domains in recent years has promoted the evolution of mobile networking and the future Internet tow…
DDPG-E2E: A Novel Policy Gradient Approach for End-to-End Communication Systems
Bolun Zhang, Nguyen Van Huynh, Dinh Thai Hoang +2
The End-to-end (E2E) learning-based approach has great potential to reshape the existing communication systems by replacing the transceivers with deep neural networks. To this end,…
Applications of Distributed Machine Learning for the Internet-of-Things: A Comprehensive Survey
Mai Le, Thien Huynh-The, Tan Do-Duy +3
The emergence of new services and applications in emerging wireless networks (e.g., beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) in th…
Semantic Communication with Probability Graph: A Joint Communication and Computation Design
Zhouxiang Zhao, Zhaohui Yang, Quoc-Viet Pham +2
In this paper, we present a probability graph-based semantic information compression system for scenarios where the base station (BS) and the user share common background knowledge…
Energy-Efficient and Real-Time Sensing for Federated Continual Learning via Sample-Driven Control
Minh Ngoc Luu, Minh-Duong Nguyen, Ebrahim Bedeer +4
An intelligent Real-Time Sensing (RTS) system must continuously acquire, update, integrate, and apply knowledge to adapt to real-world dynamics. Managing distributed intelligence i…
Revisiting LARS for Large Batch Training Generalization of Neural Networks
Khoi Do, Duong Nguyen, Hoa Nguyen +3
This paper explores Large Batch Training techniques using layer-wise adaptive scaling ratio (LARS) across diverse settings, uncovering insights. LARS algorithms with warm-up tend t…
Physical Layer Security for NOMA Systems: Requirements, Issues, and Recommendations
Saeid Pakravan, Jean-Yves Chouinard, Xingwang Li +4
Non-orthogonal multiple access (NOMA) has been viewed as a potential candidate for the upcoming generation of wireless communication systems. Comparing to traditional orthogonal mu…
Wirelessly Powered Federated Learning Networks: Joint Power Transfer, Data Sensing, Model Training, and Resource Allocation
Mai Le, Dinh Thai Hoang, Diep N. Nguyen +2
Federated learning (FL) has found many successes in wireless networks; however, the implementation of FL has been hindered by the energy limitation of mobile devices (MDs) and the…
Metaverse for Industry 5.0 in NextG Communications: Potential Applications and Future Challenges
B. Prabadevi, N. Deepa, Nancy Victor +7
With the advent of new technologies and endeavors for automation in almost all day-to-day activities, the recent discussions on the metaverse life have a greater expectation. Furth…
A Survey on Federated Learning for the Healthcare Metaverse: Concepts, Applications, Challenges, and Future Directions
Ali Kashif Bashir, Nancy Victor, Sweta Bhattacharya +7
Recent technological advancements have considerately improved healthcare systems to provide various intelligent healthcare services and improve the quality of life. Federated learn…
Distributed Machine Learning for UAV Swarms: Computing, Sensing, and Semantics
Yahao Ding, Zhaohui Yang, Quoc-Viet Pham +2
Unmanned aerial vehicle (UAV) swarms are considered as a promising technique for next-generation communication networks due to their flexibility, mobility, low cost, and the abilit…
Edge Computing for Semantic Communication Enabled Metaverse: An Incentive Mechanism Design
Nguyen Cong Luong, Quoc-Viet Pham, Thien Huynh-The +3
Semantic communication (SemCom) and edge computing are two disruptive solutions to address emerging requirements of huge data communication, bandwidth efficiency and low latency da…