219 citations · 924 across the 126 of their papers we have counts for
127 papers
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…
SecDiff: Diffusion-Aided Secure Deep Joint Source-Channel Coding Against Adversarial Attacks
Changyuan Zhao, Jiacheng Wang, Ruichen Zhang +5
Deep joint source-channel coding (JSCC) has emerged as a promising paradigm for semantic communication, delivering significant performance gains over conventional separate coding s…
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…
Temporal Spectrum Cartography in Low-Altitude Economy Networks: A Generative AI Framework with Multi-Agent Learning
Changyuan Zhao, Ruichen Zhang, Jiacheng Wang +6
This paper introduces a two-stage generative AI (GenAI) framework tailored for temporal spectrum cartography in low-altitude economy networks (LAENets). LAENets, characterized by d…
Task-Oriented Semantic Communication in Large Multimodal Models-based Vehicle Networks
Baoxia Du, Hongyang Du, Dusit Niyato +1
Task-oriented semantic communication has emerged as a fundamental approach for enhancing performance in various communication scenarios. While recent advances in Generative Artific…
Wireless Hallucination in Generative AI-enabled Communications: Concepts, Issues, and Solutions
Xudong Wang, Jiacheng Wang, Lei Feng +6
Generative AI (GenAI) is driving the intelligence of wireless communications. Due to data limitations, random generation, and dynamic environments, GenAI may generate channel infor…
AOLO: Analysis and Optimization For Low-Carbon Oriented Wireless Large Language Model Services
Xiaoqi Wang, Hongyang Du, Yuehong Gao +1
Recent advancements in large language models (LLMs) have led to their widespread adoption and large-scale deployment across various domains. However, their environmental impact, pa…
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…
Generative AI Enabled Robust Data Augmentation for Wireless Sensing in ISAC Networks
Jiacheng Wang, Changyuan Zhao, Hongyang Du +5
Integrated sensing and communication (ISAC) uses the same software and hardware resources to achieve both communication and sensing functionalities. Thus, it stands as one of the c…
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…
Generative AI Enabled Robust Sensor Placement in Cyber-Physical Power Systems: A Graph Diffusion Approach
Changyuan Zhao, Guangyuan Liu, Bin Xiang +2
With advancements in physical power systems and network technologies, integrated Cyber-Physical Power Systems (CPPS) have significantly enhanced system monitoring and control effic…
Supervised Score-Based Modeling by Gradient Boosting
Changyuan Zhao, Hongyang Du, Guangyuan Liu +1
Score-based generative models can effectively learn the distribution of data by estimating the gradient of the distribution. Due to the multi-step denoising characteristic, researc…