21 citations · 41 across the 14 of their papers we have counts for
14 papers
Dual Fluid Antenna-Assisted UAV MIMO Networks
Runke Fan, Tianheng Xu, Pei Peng +4
Fluid Antennas (FAs)-assisted Unmanned Aerial Vehicle (UAV) networks leverage the FA position adaptivity and flexible beamforming to overcome the limitations of Fixed-Positioned An…
Semantic Communications for Vehicle-Based Mission-Critical Services: Challenges and Solutions
Hui Zhou, Jiaying Guo, Marios Aristodemou +5
As mission-critical (MC) services such as Unmanned Aerial Vehicles (UAVs) based emergency communication and Internet of Vehicles (IoVs) enabled autonomous driving emerge, the tradi…
Optimizing NetGPT via Routing-Based Synergy and Reinforcement Learning
Yuxuan Chen, Rongpeng Li, Xianfu Chen +4
Large language model (LLM) agents at the network edge offer low-latency execution for routine queries. In contrast, complex requests often require the superior capability of cloud…
Robust Multi-modal Task-oriented Communications with Redundancy-aware Representations
Jingwen Fu, Ming Xiao, Zhonghao Lyu +2
Semantic communications for multi-modal data can transmit task-relevant information efficiently over noisy and bandwidth-limited channels. However, a key challenge is to simultaneo…
Service Placement and Trajectory Design for Heterogeneous Tasks in Multi-UAV Cooperative Computing Networks
Bin Li, Rongrong Yang, Lei Liu +1
In this paper, we consider deploying multiple Unmanned Aerial Vehicles (UAVs) to enhance the computation service of Mobile Edge Computing (MEC) through collaborative computation am…
DGC: Training Dynamic Graphs with Spatio-Temporal Non-Uniformity using Graph Partitioning by Chunks
Fahao Chen, Peng Li, Celimuge Wu
Dynamic Graph Neural Network (DGNN) has shown a strong capability of learning dynamic graphs by exploiting both spatial and temporal features. Although DGNN has recently received c…
Time-Critical Tasks Implementation in MEC based Multi-Robot Cooperation Systems
Rui Yin, Yineng Shen, Huawei Zhu +2
Mobile edge computing (MEC) deployment in a multi-robot cooperation (MRC) system is an effective way to accomplish the tasks in terms of energy consumption and implementation laten…
Learning-based WiFi Traffic Load Estimation in NR-U Systems
Rui Yin, Zhiqun Zou, Celimuge Wu +3
The unlicensed spectrum has been utilized to make up the shortage on frequency spectrum in new radio (NR) systems. To fully exploit the advantages brought by the unlicensed bands,…
Computation Offloading in Beyond 5G Networks: A Distributed Learning Framework and Applications
Xianfu Chen, Celimuge Wu, Zhi Liu +2
Facing the trend of merging wireless communications and multi-access edge computing (MEC), this article studies computation offloading in the beyond fifth-generation networks. To a…
Age of Information-Aware Radio Resource Management in Vehicular Networks: A Proactive Deep Reinforcement Learning Perspective
Xianfu Chen, Celimuge Wu, Tao Chen +4
In this paper, we investigate the problem of age of information (AoI)-aware radio resource management for expected long-term performance optimization in a Manhattan grid vehicle-to…
Secrecy Preserving in Stochastic Resource Orchestration for Multi-Tenancy Network Slicing
Xianfu Chen, Zhifeng Zhao, Celimuge Wu +3
Network slicing is a proposing technology to support diverse services from mobile users (MUs) over a common physical network infrastructure. In this paper, we consider radio access…
Decentralized Deep Reinforcement Learning for Delay-Power Tradeoff in Vehicular Communications
Xianfu Chen, Celimuge Wu, Honggang Zhang +3
This paper targets at the problem of radio resource management for expected long-term delay-power tradeoff in vehicular communications. At each decision epoch, the road side unit o…
Multipath Transmission Scheduling in Millimeter Wave Cloud Radio Access Networks
Xianfu Chen, Pei Liu, Hang Liu +2
Millimeter wave (mmWave) communications provide great potential for next-generation cellular networks to meet the demands of fast-growing mobile data traffic with plentiful spectru…
Performance Optimization in Mobile-Edge Computing via Deep Reinforcement Learning
Xianfu Chen, Honggang Zhang, Celimuge Wu +3
To improve the quality of computation experience for mobile devices, mobile-edge computing (MEC) is emerging as a promising paradigm by providing computing capabilities within radi…