60 citations · 146 across the 12 of their papers we have counts for
13 papers
DS-Net: A Dynamic Split Network for Edge-Cloud Collaborative Inference
Xinyun Zhang, Li Wang, Lei Jin +2
Collaborative inference serves as a critical methodology in edge intelligence. Existing collaborative inference methods operate by splitting the deep neural network (DNN) model bet…
Deep Reinforcement Learning based Joint Spectrum Allocation and Configuration Design for STAR-RIS-Assisted V2X Communications
Pyae Sone Aung, Loc X. Nguyen, Yan Kyaw Tun +2
Vehicle-to-Everything (V2X) communications play a crucial role in ensuring safe and efficient modern transportation systems. However, challenges arise in scenarios with buildings,…
SpaceRIS: LEO Satellite Coverage Maximization in 6G Sub-THz Networks by MAPPO DRL and Whale Optimization
Sheikh Salman Hassan, Yu Min Park, Yan Kyaw Tun +3
Satellite systems face a significant challenge in effectively utilizing limited communication resources to meet the demands of ground network traffic, characterized by asymmetrical…
Swin Transformer-Based Dynamic Semantic Communication for Multi-User with Different Computing Capacity
Loc X. Nguyen, Ye Lin Tun, Yan Kyaw Tun +4
Semantic communication has gained significant attention from researchers as a promising technique to replace conventional communication in the next generation of communication syst…
Satellite-based ITS Data Offloading & Computation in 6G Networks: A Cooperative Multi-Agent Proximal Policy Optimization DRL with Attention Approach
Sheikh Salman Hassan, Yu Min Park, Yan Kyaw Tun +3
The proliferation of intelligent transportation systems (ITS) has led to increasing demand for diverse network applications. However, conventional terrestrial access networks (TANs…
Joint Trajectory and Resource Optimization of MEC-Assisted UAVs in Sub-THz Networks: A Resources-based Multi-Agent Proximal Policy Optimization DRL with Attention Mechanism
Yu Min Park, Sheikh Salman Hassan, Yan Kyaw Tun +2
THz band communication technology will be used in the 6G networks to enable high-speed and high-capacity data service demands. However, THz-communication losses arise owing to limi…
Federated Learning for Digital Twin-Based Vehicular Networks: Architecture and Challenges
Latif U. Khan, Ehzaz Mustafa, Junaid Shuja +4
Emerging intelligent transportation applications, such as accident reporting, lane change assistance, collision avoidance, and infotainment, will be based on diverse requirements (…
Energy-Efficient Communication Networks via Multiple Aerial Reconfigurable Intelligent Surfaces: DRL and Optimization Approach
Pyae Sone Aung, Yu Min Park, Yan Kyaw Tun +2
In the realm of wireless communications in 5G, 6G and beyond, deploying unmanned aerial vehicle (UAV) has been an innovative approach to extend the coverage area due to its easy de…
Deep Reinforcement Learning Coordinated Receiver Beamforming for Millimeter-Wave Train-ground Communications
Xutao Zhou, Xiangfei Zhang, Chen Chen +6
As more and more people choose high-speed rail (HSR) as a means of transportation for short trips, there is ever growing demand of high quality of multimedia services. With its ric…
3TO: THz-Enabled Throughput and Trajectory Optimization of UAVs in 6G Networks by Proximal Policy Optimization Deep Reinforcement Learning
Sheikh Salman Hassan, Yu Min Park, Yan Kyaw Tun +3
Next-generation networks need to meet ubiquitous and high data-rate demand. Therefore, this paper considers the throughput and trajectory optimization of terahertz (THz)-enabled un…
Blue Data Computation Maximization in 6G Space-Air-Sea Non-Terrestrial Networks
Sheikh Salman Hassan, Yan Kyaw Tun, Walid Saad +2
Non-terrestrial networks (NTN), encompassing space and air platforms, are a key component of the upcoming sixth-generation (6G) cellular network. Meanwhile, maritime network traffi…
Trajectory Optimization and Phase-Shift Design in IRS Assisted UAV Network for High Speed Trains
Yu Min Park, Yan Kyaw Tun, Zhu Han +1
The recent trend towards the high-speed transportation system has spurred the development of high-speed trains (HSTs). However, enabling HST users with seamless wireless connectivi…
Adaptive Stochastic ADMM for Decentralized Reinforcement Learning in Edge Industrial IoT
Wanlu Lei, Yu Ye, Ming Xiao +2
Edge computing provides a promising paradigm to support the implementation of Industrial Internet of Things (IIoT) by offloading tasks to nearby edge nodes. Meanwhile, the increasi…