219 citations · 924 across the 126 of their papers we have counts for
58 papers · 1 filter
Large Language Model (LLM)-enabled Reinforcement Learning for Wireless Network Optimization
Jie Zheng, Ruichen Zhang, Dusit Niyato +5
Enhancing future wireless networks presents a significant challenge for networking systems due to diverse user demands and the emergence of 6G technology. While reinforcement learn…
LLM-Empowered Agentic AI for QoE-Aware Network Slicing Management in Industrial IoT
Xudong Wang, Lei Feng, Ruichen Zhang +6
The Industrial Internet of Things (IIoT) requires networks that deliver ultra-low latency, high reliability, and cost efficiency, which traditional optimization methods and deep re…
Optimizing Split Federated Learning with Unstable Client Participation
Wei Wei, Zheng Lin, Xihui Liu +3
To enable training of large artificial intelligence (AI) models at the network edge, split federated learning (SFL) has emerged as a promising approach by distributing computation…
Secure Multi-LLM Agentic AI and Agentification for Edge General Intelligence by Zero-Trust: A Survey
Yinqiu Liu, Ruichen Zhang, Haoxiang Luo +9
Agentification serves as a critical enabler of Edge General Intelligence (EGI), transforming massive edge devices into cognitive agents through integrating Large Language Models (L…
Energy-Efficient RSMA-enabled Low-altitude MEC Optimization Via Generative AI-enhanced Deep Reinforcement Learning
Xudong Wang, Hongyang Du, Lei Feng +1
The growing demand for low-latency computing in 6G is driving the use of UAV-based low-altitude mobile edge computing (MEC) systems. However, limited spectrum often leads to severe…
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…
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…
Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences
Adnan Shahid, Adrian Kliks, Ahmed Al-Tahmeesschi +132
This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions…
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…
Multi-objective Low-altitude IRS-assisted ISAC Optimization via Generative AI-enhanced Deep Reinforcement Learning
Wenwen Xie, Geng Sun, Chuang Zhang +3
Integrated sensing and communication (ISAC) has garnered substantial research interest owing to its pivotal role in advancing the development of next-generation (6G) wireless netwo…
Contract-Inspired Contest Theory for Controllable Image Generation in Mobile Edge Metaverse
Guangyuan Liu, Hongyang Du, Jiacheng Wang +2
The rapid advancement of immersive technologies has propelled the development of the Metaverse, where the convergence of virtual and physical realities necessitates the generation…
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…
Online Collaborative Resource Allocation and Task Offloading for Multi-access Edge Computing
Geng Sun, Minghua Yuan, Zemin Sun +5
Multi-access edge computing (MEC) is emerging as a promising paradigm to provide flexible computing services close to user devices (UDs). However, meeting the computation-hungry an…
Joint Optimization of UAV-Carried IRS for Urban Low Altitude mmWave Communications with Deep Reinforcement Learning
Wenwen Xie, Geng Sun, Bei Liu +5
Emerging technologies in sixth generation (6G) of wireless communications, such as terahertz communication and ultra-massive multiple-input multiple-output, present promising prosp…
Embodied AI-Enhanced Vehicular Networks: An Integrated Large Language Models and Reinforcement Learning Method
Ruichen Zhang, Changyuan Zhao, Hongyang Du +5
This paper investigates adaptive transmission strategies in embodied AI-enhanced vehicular networks by integrating large language models (LLMs) for semantic information extraction…
Joint Model Caching and Resource Allocation in Generative AI-Enabled Wireless Edge Networks
Zhang Liu, Hongyang Du, Lianfen Huang +2
With the rapid advancement of artificial intelligence (AI), generative AI (GenAI) has emerged as a transformative tool, enabling customized and personalized AI-generated content (A…
Generative AI Enabled Matching for 6G Multiple Access
Xudong Wang, Hongyang Du, Dusit Niyato +5
In wireless networks, applying deep learning models to solve matching problems between different entities has become a mainstream and effective approach. However, the complex netwo…
Toward Mixture-of-Experts Enabled Trustworthy Semantic Communication for 6G Networks
Jiayi He, Xiaofeng Luo, Jiawen Kang +5
Semantic Communication (SemCom) plays a pivotal role in 6G networks, offering a viable solution for future efficient communication. Deep Learning (DL)-based semantic codecs further…
CSQF-based Time-Sensitive Flow Scheduling in Long-distance Industrial IoT Networks
Yudong Huang, Tao Huang, Xinyuan Zhang +4
Booming time-critical services, such as automated manufacturing and remote operations, stipulate increasing demands for facilitating large-scale Industrial Internet of Things (IoT)…
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…
Generative AI for Energy Harvesting Internet of Things Network: Fundamental, Applications, and Opportunities
Wenwen Xie, Geng Sun, Jiahui Li +4
Internet of Things (IoT) devices are typically powered by small-sized batteries with limited energy storage capacity, requiring regular replacement or recharging. To reduce costs a…
Enhancing Wireless Networks with Attention Mechanisms: Insights from Mobile Crowdsensing
Yaoqi Yang, Hongyang Du, Zehui Xiong +3
The increasing demand for sensing, collecting, transmitting, and processing vast amounts of data poses significant challenges for resource-constrained mobile users, thereby impacti…
Optimizing Generative AI Networking: A Dual Perspective with Multi-Agent Systems and Mixture of Experts
Ruichen Zhang, Hongyang Du, Dusit Niyato +4
In the continued development of next-generation networking and artificial intelligence content generation (AIGC) services, the integration of multi-agent systems (MAS) and the mixt…