43 citations · 66 across the 15 of their papers we have counts for
17 papers
Energy Saving in 5G and Beyond Networks: A Quantum Reinforcement Learning Approach
Muhammad Usman, Nguyen Van Huynh, Marianna Lezzi +1
Energy saving has become a critical challenge in 5G and beyond networks. The rapid growth of connected devices has increased the overall network energy demand, driving operational…
JEPA for AI-Native 6G: Predictive Representations and Open Challenges
Sheikh Salman Hassan, Irshad A. Meer, Almoatssimbillah Saifaldawla +9
Sixth-generation (6G) networks are moving toward AI-native operation, where learning modules are embedded across the radio access network (RAN), edge, and core. This transition req…
Collaborative Intelligence for UAV-Satellite Network Slicing: Towards a Joint QoS-Energy-Fairness MADRL Optimization
Thanh-Dao Nguyen, Ngoc-Tan Nguyen, Thai-Duong Nguyen +3
Non terrestrial networks are critical for achieving global 6G coverage, yet efficient resource management in aerial and space environments remains challenging due to limited onboar…
Joint Beamforming and Trajectory Optimization for Multi-UAV-Assisted Integrated Sensing and Communication Systems
Yan Kyaw Tun, Nway Nway Ei, Sheikh Salman Hassan +4
In this paper, we investigate beamforming design and trajectory optimization for a multi-unmanned aerial vehicle (UAV)-assisted integrated sensing and communication (ISAC) system.…
A Universal Deep Neural Network for Signal Detection in Wireless Communication Systems
Khalid Albagami, Nguyen Van Huynh, Geoffrey Ye Li
Recently, deep learning (DL) has been emerging as a promising approach for channel estimation and signal detection in wireless communications. The majority of the existing studies…
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…
Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunities
Guangyuan Liu, Nguyen Van Huynh, Hongyang Du +7
With recent advances in artificial intelligence (AI) and robotics, unmanned vehicle swarms have received great attention from both academia and industry due to their potential to p…
Generative AI for Physical Layer Communications: A Survey
Nguyen Van Huynh, Jiacheng Wang, Hongyang Du +5
The recent evolution of generative artificial intelligence (GAI) leads to the emergence of groundbreaking applications such as ChatGPT, which not only enhances the efficiency of di…
Securing MIMO Wiretap Channel with Learning-Based Friendly Jamming under Imperfect CSI
Bui Minh Tuan, Diep N. Nguyen, Nguyen Linh Trung +5
Wireless communications are particularly vulnerable to eavesdropping attacks due to their broadcast nature. To effectively deal with eavesdroppers, existing security techniques usu…
Countering Eavesdroppers with Meta-learning-based Cooperative Ambient Backscatter Communications
Nam H. Chu, Nguyen Van Huynh, Diep N. Nguyen +5
This article introduces a novel lightweight framework using ambient backscattering communications to counter eavesdroppers. In particular, our framework divides an original message…
Deep Deterministic Policy Gradient for End-to-End Communication Systems without Prior Channel Knowledge
Bolun Zhang, Nguyen Van Huynh
End-to-End (E2E) learning-based concept has been recently introduced to jointly optimize both the transmitter and the receiver in wireless communication systems. Unfortunately, thi…
Distributed-Training-and-Execution Multi-Agent Reinforcement Learning for Power Control in HetNet
Kaidi Xu, Nguyen Van Huynh, Geoffrey Ye Li
In heterogeneous networks (HetNets), the overlap of small cells and the macro cell causes severe cross-tier interference. Although there exist some approaches to address this probl…
DeepFake: Deep Dueling-based Deception Strategy to Defeat Reactive Jammers
Nguyen Van Huynh, Dinh Thai Hoang, Diep N. Nguyen +1
In this paper, we introduce DeepFake, a novel deep reinforcement learning-based deception strategy to deal with reactive jamming attacks. In particular, for a smart and reactive ja…
Optimal Beam Association for High Mobility mmWave Vehicular Networks: Lightweight Parallel Reinforcement Learning Approach
Nguyen Van Huynh, Diep N. Nguyen, Dinh Thai Hoang +1
In intelligent transportation systems (ITS), vehicles are expected to feature with advanced applications and services which demand ultra-high data rates and low-latency communicati…
"Jam Me If You Can'': Defeating Jammer with Deep Dueling Neural Network Architecture and Ambient Backscattering Augmented Communications
Nguyen Van Huynh, Diep N. Nguyen, Dinh Thai Hoang +1
With conventional anti-jamming solutions like frequency hopping or spread spectrum, legitimate transceivers often tend to "escape" or "hide" themselves from jammers. These reactive…
Offloading Energy Efficiency with Delay Constraint for Cooperative Mobile Edge Computing Networks
Thai T. Vu, Nguyen Van Huynh, Dinh Thai Hoang +2
We propose a novel edge computing network architecture that enables edge nodes to cooperate in sharing computing and radio resources to minimize the total energy consumption of mob…
Reinforcement Learning Approach for RF-Powered Cognitive Radio Network with Ambient Backscatter
Nguyen Van Huynh, Dinh Thai Hoang, Diep N. Nguyen +3
For an RF-powered cognitive radio network with ambient backscattering capability, while the primary channel is busy, the RF-powered secondary user (RSU) can either backscatter the…