219 citations · 385 across the 32 of their papers we have counts for
26 papers · 1 filter
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…
Collaborative Charging Optimization for Wireless Rechargeable Sensor Networks via Heterogeneous Mobile Chargers
Jianhang Yao, Hui Kang, Geng Sun +4
Despite the rapid proliferation of Internet of Things applications driving widespread wireless sensor network (WSN) deployment, traditional WSNs remain fundamentally constrained by…
A Synergy of Computing Power Networks and Low-Altitude Economy Intelligent Communications: Challenges, Design Principles, and Research Directions
Yan Sun, Yinqiu Liu, Shaoyong Guo +7
The rapid development of the Low-Altitude Economy (LAE) has created opportunities for emerging services such as autonomous aerial transportation, aerial sensing, and emergency resp…
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…
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…
Toward Edge General Intelligence with Multiple-Large Language Model (Multi-LLM): Architecture, Trust, and Orchestration
Haoxiang Luo, Yinqiu Liu, Ruichen Zhang +7
Edge computing enables real-time data processing closer to its source, thus improving the latency and performance of edge-enabled AI applications. However, traditional AI models of…
Wireless Agentic AI with Retrieval-Augmented Multimodal Semantic Perception
Guangyuan Liu, Yinqiu Liu, Ruichen Zhang +5
The rapid development of multimodal AI and Large Language Models (LLMs) has greatly enhanced real-time interaction, decision-making, and collaborative tasks. However, in wireless m…
Context-Aware Semantic Communication for the Wireless Networks
Guangyuan Liu, Yinqiu Liu, Jiacheng Wang +5
In next-generation wireless networks, supporting real-time applications such as augmented reality, autonomous driving, and immersive Metaverse services demands stringent constraint…
LAMeTA: Intent-Aware Agentic Network Optimization via a Large AI Model-Empowered Two-Stage Approach
Yinqiu Liu, Guangyuan Liu, Jiacheng Wang +5
Nowadays, Generative AI (GenAI) reshapes numerous domains by enabling machines to create content across modalities. As GenAI evolves into autonomous agents capable of reasoning, co…
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…
A Trustworthy Multi-LLM Network: Challenges,Solutions, and A Use Case
Haoxiang Luo, Gang Sun, Yinqiu Liu +4
Large Language Models (LLMs) demonstrate strong potential across a variety of tasks in communications and networking due to their advanced reasoning capabilities. However, because…
Covert Prompt Transmission for Secure Large Language Model Services
Ruichen Zhang, Yinqiu Liu, Shunpu Tang +5
This paper investigates covert prompt transmission for secure and efficient large language model (LLM) services over wireless networks. We formulate a latency minimization problem…
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…
Intelligent Mobile AI-Generated Content Services via Interactive Prompt Engineering and Dynamic Service Provisioning
Yinqiu Liu, Ruichen Zhang, Jiacheng Wang +4
Due to massive computational demands of large generative models, AI-Generated Content (AIGC) can organize collaborative Mobile AIGC Service Providers (MASPs) at network edges to pr…
Adaptive Contextual Caching for Mobile Edge Large Language Model Service
Guangyuan Liu, Yinqiu Liu, Jiacheng Wang +4
Mobile edge Large Language Model (LLM) deployments face inherent constraints, such as limited computational resources and network bandwidth. Although Retrieval-Augmented Generation…
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…
Generative AI in Data Center Networking: Fundamentals, Perspectives, and Case Study
Yinqiu Liu, Hongyang Du, Dusit Niyato +4
Generative AI (GenAI), exemplified by Large Language Models (LLMs) such as OpenAI's ChatGPT, is revolutionizing various fields. Central to this transformation is Data Center Networ…
Empowering Wireless Networks with Artificial Intelligence Generated Graph
Jiacheng Wang, Yinqiu Liu, Hongyang Du +4
In wireless communications, transforming network into graphs and processing them using deep learning models, such as Graph Neural Networks (GNNs), is one of the mainstream network…
Cross-Modal Generative Semantic Communications for Mobile AIGC: Joint Semantic Encoding and Prompt Engineering
Yinqiu Liu, Hongyang Du, Dusit Niyato +5
Employing massive Mobile AI-Generated Content (AIGC) Service Providers (MASPs) with powerful models, high-quality AIGC services can become accessible for resource-constrained end u…
ProSecutor: Protecting Mobile AIGC Services on Two-Layer Blockchain via Reputation and Contract Theoretic Approaches
Yinqiu Liu, Hongyang Du, Dusit Niyato +5
Mobile AI-Generated Content (AIGC) has achieved great attention in unleashing the power of generative AI and scaling the AIGC services. By employing numerous Mobile AIGC Service Pr…
Defining Problem from Solutions: Inverse Reinforcement Learning (IRL) and Its Applications for Next-Generation Networking
Yinqiu Liu, Ruichen Zhang, Hongyang Du +4
Performance optimization is a critical concern in networking, on which Deep Reinforcement Learning (DRL) has achieved great success. Nonetheless, DRL training relies on precisely d…
Generative AI Agents with Large Language Model for Satellite Networks via a Mixture of Experts Transmission
Ruichen Zhang, Hongyang Du, Yinqiu Liu +5
In response to the needs of 6G global communications, satellite communication networks have emerged as a key solution. However, the large-scale development of satellite communicati…
Interactive AI with Retrieval-Augmented Generation for Next Generation Networking
Ruichen Zhang, Hongyang Du, Yinqiu Liu +5
With the advance of artificial intelligence (AI), the emergence of Google Gemini and OpenAI Q* marks the direction towards artificial general intelligence (AGI). To implement AGI,…
Optimizing Mobile-Edge AI-Generated Everything (AIGX) Services by Prompt Engineering: Fundamental, Framework, and Case Study
Yinqiu Liu, Hongyang Du, Dusit Niyato +4
As the next-generation paradigm for content creation, AI-Generated Content (AIGC), i.e., generating content automatically by Generative AI (GAI) based on user prompts, has gained g…