7 citations · 37 across the 44 of their papers we have counts for
30 papers · 1 filter
Low-Altitude Satellite-AAV Collaborative Joint Mobile Edge Computing and Data Collection via Diffusion-based Deep Reinforcement Learning
Boxiong Wang, Hui Kang, Jiahui Li +5
The integration of satellite and autonomous aerial vehicle (AAV) communications has become essential for the scenarios requiring both wide coverage and rapid deployment, particular…
Encrypted Traffic Detection in Resource Constrained IoT Networks: A Diffusion Model and LLM Integrated Framework
Hongjuan Li, Hui Kang, Chenbang Liu +6
The proliferation of Internet-of-things (IoT) infrastructures and the widespread adoption of traffic encryption present significant challenges, particularly in environments charact…
Tutorial on Large Language Model-Enhanced Reinforcement Learning for Wireless Networks
Lingyi Cai, Wenjie Fu, Yuxi Huang +9
Reinforcement Learning (RL) has shown remarkable success in enabling adaptive and data-driven optimization for various applications in wireless networks. However, classical RL suff…
Hierarchical Online Optimization Approach for IRS-enabled Low-altitude MEC in Vehicular Networks
Yixian Wang, Geng Sun, Zemin Sun +2
In this paper, we propose an intelligent reflecting surface (IRS)-enabled low-altitude multi-access edge computing (MEC) architecture, where an aerial MEC server cooperates with a…
Low-Altitude UAV-Carried Movable Antenna for Joint Wireless Power Transfer and Covert Communications
Chuang Zhang, Geng Sun, Jiahui Li +5
The proliferation of Internet of Things (IoT) networks has created an urgent need for sustainable energy solutions, particularly for the battery-constrained spatially distributed I…
When UAV Swarm Meets IRS: Collaborative Secure Communications in Low-altitude Wireless Networks
Jiahui Li, Xinyue Liang, Geng Sun +5
Low-altitude wireless networks (LAWNs) represent a promising architecture that integrates unmanned aerial vehicles (UAVs) as aerial nodes to provide enhanced coverage, reliability,…
RIS-assisted Data Collection and Wireless Power Transfer in Low-altitude Wireless Networks
Wenwen Xie, Geng Sun, Jiahui Li +5
Low-altitude wireless networks (LAWNs) have become effective solutions for collecting data from low-power Internet-of-Things devices (IoTDs) in remote areas with limited communicat…
AI Reasoning for Wireless Communications and Networking: A Survey and Perspectives
Haoxiang Luo, Yu Yan, Yanhui Bian +9
Artificial Intelligence (AI) techniques play a pivotal role in optimizing wireless communication networks. However, traditional deep learning approaches often act as closed boxes,…
Large Language Models for Next-Generation Wireless Network Management: A Survey and Tutorial
Bisheng Wei, Ruihong Jiang, Ruichen Zhang +9
The rapid advancement toward sixth-generation (6G) wireless networks has significantly intensified the complexity and scale of optimization problems, including resource allocation…
Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions
Ruichen Zhang, Guangyuan Liu, Yinqiu Liu +10
The rapid expansion of sixth-generation (6G) wireless networks and the Internet of Things (IoT) has catalyzed the evolution from centralized cloud intelligence towards decentralize…
Safeguarding ISAC Performance in Low-Altitude Wireless Networks Under Channel Access Attack
Jiacheng Wang, Jialing He, Geng Sun +5
The increasing saturation of terrestrial resources has driven the exploration of low-altitude applications such as air taxis. Low altitude wireless networks (LAWNs) serve as the fo…
Chain-of-Thought for Large Language Model-empowered Wireless Communications
Xudong Wang, Jian Zhu, Ruichen Zhang +6
Recent advances in large language models (LLMs) have opened new possibilities for automated reasoning and decision-making in wireless networks. However, applying LLMs to wireless c…
Forewarned is Forearmed: A Survey on Large Language Model-based Agents in Autonomous Cyberattacks
Minrui Xu, Jiani Fan, Xinyu Huang +8
With the continuous evolution of Large Language Models (LLMs), LLM-based agents have advanced beyond passive chatbots to become autonomous cyber entities capable of performing comp…
LLM-guided DRL for Multi-tier LEO Satellite Networks with Hybrid FSO/RF Links
Jiahui Li, Geng Sun, Zemin Sun +5
Despite significant advancements in terrestrial networks, inherent limitations persist in providing reliable coverage to remote areas and maintaining resilience during natural disa…
Mixture of Experts for Decentralized Generative AI and Reinforcement Learning in Wireless Networks: A Comprehensive Survey
Yunting Xu, Jiacheng Wang, Ruichen Zhang +10
Mixture of Experts (MoE) has emerged as a promising paradigm for scaling model capacity while preserving computational efficiency, particularly in large-scale machine learning arch…
Efficient Twin Migration in Vehicular Metaverses: Multi-Agent Split Deep Reinforcement Learning with Spatio-Temporal Trajectory Generation
Junlong Chen, Jiawen Kang, Minrui Xu +5
Vehicle Twins (VTs) as digital representations of vehicles can provide users with immersive experiences in vehicular metaverse applications, e.g., Augmented Reality (AR) navigation…
Toward Agentic AI: Generative Information Retrieval Inspired Intelligent Communications and Networking
Ruichen Zhang, Shunpu Tang, Yinqiu Liu +5
The increasing complexity and scale of modern telecommunications networks demand intelligent automation to enhance efficiency, adaptability, and resilience. Agentic AI has emerged…
Retrieval-augmented Generation for GenAI-enabled Semantic Communications
Shunpu Tang, Ruichen Zhang, Yuxuan Yan +4
Semantic communication (SemCom) is an emerging paradigm aiming at transmitting only task-relevant semantic information to the receiver, which can significantly improve communicatio…
When Graph Meets Retrieval Augmented Generation for Wireless Networks: A Tutorial and Case Study
Yang Xiong, Ruichen Zhang, Yinqiu Liu +4
The rapid development of next-generation networking technologies underscores their transformative role in revolutionizing modern communication systems, enabling faster, more reliab…
JC5A: Service Delay Minimization for Aerial MEC-assisted Industrial Cyber-Physical Systems
Geng Sun, Jiaxu Wu, Zemin Sun +5
In the era of the sixth generation (6G) and industrial Internet of Things (IIoT), an industrial cyber-physical system (ICPS) drives the proliferation of sensor devices and computin…
Efficient Multi-user Offloading of Personalized Diffusion Models: A DRL-Convex Hybrid Solution
Wanting Yang, Zehui Xiong, Song Guo +3
With the impressive generative capabilities of diffusion models, personalized content synthesis has emerged as the most highly anticipated. However, the large model sizes and itera…
Diffusion-based Auction Mechanism for Efficient Resource Management in 6G-enabled Vehicular Metaverses
Jiawen Kang, Yongju Tong, Yue Zhong +5
The rise of 6G-enable Vehicular Metaverses is transforming the automotive industry by integrating immersive, real-time vehicular services through ultra-low latency and high bandwid…
Rethinking Generative Semantic Communication for Multi-User Systems with Large Language Models
Wanting Yang, Zehui Xiong, Shiwen Mao +4
The surge in connected devices in 6G with typical complex tasks requiring multi-user cooperation, such as smart agriculture and smart cities, poses significant challenges to unsust…
Sustainable Diffusion-based Incentive Mechanism for Generative AI-driven Digital Twins in Industrial Cyber-Physical Systems
Jinbo Wen, Jiawen Kang, Dusit Niyato +2
Industrial Cyber-Physical Systems (ICPSs) are an integral component of modern manufacturing and industries. By digitizing data throughout product life cycles, Digital Twins (DTs) i…