117 citations · 195 across the 62 of their papers we have counts for
32 papers · 1 filter
Agentic-SecPBFT: Agentic AI-Driven Proactive Security Framework for Wireless PBFT Consensus in Mobile Ad-Hoc Networks
Haoxiang Luo, Yinqiu Liu, Ruichen Zhang +5
The standard Practical Byzantine Fault Tolerance (PBFT) protocol, designed for stable, wired environments, exhibits critical vulnerabilities when deployed in settings like mobile a…
SkyChain Intelligence: A Blockchain-Secured Multi-Agent DRL Framework for Low-Altitude Embodied Artificial Intelligence
Haoxiang Luo, Tianqi Jiang, Ruichen Zhang +5
With the rapid development of the Low-Altitude Economy (LAE) ecosystem, Low-Altitude Embodied Artificial Intelligence (LAEAI) agents have become the core carriers of autonomous aer…
Unleashing Tool Engineering and Intelligence for Agentic AI in Next-Generation Communication Networks
Yinqiu Liu, Ruichen Zhang, Dusit Niyato +3
Nowadays, agentic AI is emerging as a transformative paradigm for next-generation communication networks, promising to evolve large language models (LLMs) from passive chatbots int…
Cross-reality location privacy protection in 6G-enabled vehicular metaverses: an LLM-enhanced hybrid generative diffusion model-based approach
Xiaofeng Luo, Jiayi He, Jiawen Kang +4
The emergence of 6G-enabled vehicular metaverses enables Autonomous Vehicles (AVs) to operate across physical and virtual spaces through space-air-ground-sea integrated networks. T…
Wireless Copilot: An AI-Powered Partner for Navigating Next-Generation Wireless Complexity
Haoxiang Luo, Ruichen Zhang, Yinqiu Liu +3
The sixth-generation (6G) of wireless networks introduces a level of operational complexity that exceeds the limits of traditional automation and manual oversight. This paper intro…
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…
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…
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…
Hybrid Reinforcement Learning-based Sustainable Multi-User Computation Offloading for Mobile Edge-Quantum Computing
Minrui Xu, Dusit Niyato, Jiawen Kang +5
Exploiting quantum computing at the mobile edge holds immense potential for facilitating large-scale network design, processing multimodal data, optimizing resource management, and…
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…
Generative Artificial Intelligence for Beamforming in Low-Altitude Economy
Geng Sun, Jia Qi, Chuang Zhang +5
The growth of low-altitude economy (LAE) has driven a rising demand for efficient and secure communication. However, conventional beamforming optimization techniques struggle in th…
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…
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…
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…
Hallucination-aware Optimization for Large Language Model-empowered Communications
Yinqiu Liu, Guangyuan Liu, Ruichen Zhang +5
Large Language Models (LLMs) have significantly advanced communications fields, such as Telecom Q\&A, mathematical modeling, and coding. However, LLMs encounter an inherent issue k…
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…
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…
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…
Integration of Mixture of Experts and Multimodal Generative AI in Internet of Vehicles: A Survey
Minrui Xu, Dusit Niyato, Jiawen Kang +6
Generative AI (GAI) can enhance the cognitive, reasoning, and planning capabilities of intelligent modules in the Internet of Vehicles (IoV) by synthesizing augmented datasets, com…
Fusion of Mixture of Experts and Generative Artificial Intelligence in Mobile Edge Metaverse
Guangyuan Liu, Hongyang Du, Dusit Niyato +5
In the digital transformation era, Metaverse offers a fusion of virtual reality (VR), augmented reality (AR), and web technologies to create immersive digital experiences. However,…
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…