117 citations · 125 across the 15 of their papers we have counts for
15 papers
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…
DWM-RO: Decentralized World Models with Reasoning Offloading for SWIPT-enabled Satellite-Terrestrial HetNets
Guangyuan Liu, Yinqiu Liu, Ruichen Zhang +5
Wireless networks are undergoing a paradigm shift toward massive connectivity with energy-efficient operation, driving the integration of satellite-terrestrial architectures with s…
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…
Graph Diffusion-Based AeBS Deployment and Resource Allocation in RSMA-Enabled URLLC Low-Altitude Wireless Networks
Xudong Wang, Lei Feng, Jiacheng Wang +4
As a key component of low-altitude wireless networks, aerial base stations (AeBSs) provide flexible and reliable wireless coverage to support 6G ultra-reliable and low-latency comm…
Generative AI for Data Augmentation in Wireless Networks: Analysis, Applications, and Case Study
Jinbo Wen, Jiawen Kang, Dusit Niyato +4
Data augmentation as a technique can mitigate data scarcity in machine learning. However, owing to fundamental differences in wireless data structures, traditional data augmentatio…
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…
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…
Generative AI for Advanced UAV Networking
Geng Sun, Wenwen Xie, Dusit Niyato +5
With the impressive achievements of chatGPT and Sora, generative artificial intelligence (GAI) has received increasing attention. Not limited to the field of content generation, GA…
MOC-RVQ: Multilevel Codebook-Assisted Digital Generative Semantic Communication
Yingbin Zhou, Yaping Sun, Guanying Chen +5
Vector quantization-based image semantic communication systems have successfully boosted transmission efficiency, but face challenges with conflicting requirements between codebook…
The Age of Generative AI and AI-Generated Everything
Hongyang Du, Dusit Niyato, Jiawen Kang +9
Generative AI (GAI) has emerged as a significant advancement in artificial intelligence, renowned for its language and image generation capabilities. This paper presents ``AI-Gener…
Knowledge Base Enabled Semantic Communication: A Generative Perspective
Jinke Ren, Zezhong Zhang, Jie Xu +4
Semantic communication is widely touted as a key technology for propelling the sixth-generation (6G) wireless networks. However, providing effective semantic representation is quit…
Generative AI for Space-Air-Ground Integrated Networks
Ruichen Zhang, Hongyang Du, Dusit Niyato +5
Recently, generative AI technologies have emerged as a significant advancement in artificial intelligence field, renowned for their language and image generation capabilities. Mean…
Generative AI for Integrated Sensing and Communication: Insights from the Physical Layer Perspective
Jiacheng Wang, Hongyang Du, Dusit Niyato +4
As generative artificial intelligence (GAI) models continue to evolve, their generative capabilities are increasingly enhanced and being used extensively in content generation. Bey…
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…