3 citations · 4 across the 12 of their papers we have counts for
12 papers
Agentic AI for Bilevel Long-Term Optimization of Policy-Driven Physical Layer Systems
Bingnan Xiao, Chenhao Yang, Wei Ni +2
Network operators' changing policies, service requirements, and stringent real-time constraints render existing methods designed with fixed objectives and constraints ineffective.…
Priority-Aware Learning-Unlearning Correction for Dynamic Decentralized LoRA Fine-Tuning
Nuocheng Yang, Yechen He, Sihua Wang +3
As large language models (LLMs) are increasingly deployed at the network edge to provide pervasive generative AI services, decentralized federated learning (DFL) provides a vital m…
Accelerating Privacy-Preserving Federated Learning in Large-Scale LEO Satellite Systems
Binquan Guo, Junteng Cao, Marie Siew +3
Large-scale low-Earth-orbit (LEO) satellite systems are increasingly valued for their ability to enable rapid and wide-area data exchange, thereby facilitating the collaborative tr…
Enhancing Mega-Satellite Networks with Generative Semantic Communication: A Networking Perspective
Binquan Guo, Wanting Yang, Zehui Xiong +5
The advance of direct satellite-to-device communication has positioned mega-satellite constellations as a cornerstone of 6G wireless communication, enabling seamless global connect…
Multi-User Generative Semantic Communication with Intent-Aware Semantic-Splitting Multiple Access
Jiayi Lu, Wanting Yang, Zehui Xiong +4
With the booming development of generative artificial intelligence (GAI), semantic communication (SemCom) has emerged as a new paradigm for reliable and efficient communication. Th…
Bridging the Modality Gap: Enhancing Channel Prediction with Semantically Aligned LLMs and Knowledge Distillation
Zhaoyang Li, Qianqian Yang, Zehui Xiong +2
Accurate channel prediction is essential in massive multiple-input multiple-output (m-MIMO) systems to improve precoding effectiveness and reduce the overhead of channel state info…
Memristor-Based Meta-Learning for Fast mmWave Beam Prediction in Non-Stationary Environments
Yuwen Cao, Tomoaki Ohtsuki, Setareh Maghsudi +1
Traditional machine learning techniques have achieved great success in improving data-rate performance and reducing latency in millimeter wave (mmWave) communications. However, the…
Generative AI-Enhanced Multi-Modal Semantic Communication in Internet of Vehicles: System Design and Methodologies
Jiayi Lu, Wanting Yang, Zehui Xiong +4
Vehicle-to-everything (V2X) communication supports numerous tasks, from driving safety to entertainment services. To achieve a holistic view, vehicles are typically equipped with m…
Rethinking Generative Semantic Communication for Multi-User Systems with Large Language Models
Wanting Yang, Zehui Xiong, Shiwen Mao +4
The surge in connected devices in 6G with typical complex tasks requiring multi-user cooperation, such as smart agriculture and smart cities, poses significant challenges to unsust…
FAST: Flexible and Adaptive Semantic Transmission for Resource-constrained Multi-user Generative Semantic Communication
Yiru Wang, Wanting Yang, Fangli Mou +4
The rapid advancement of generative artificial intelligence has spurred innovative approaches to semantic communication, giving rise to a new paradigm known as generative semantic…
Semantic Change Driven Generative Semantic Communication Framework
Wanting Yang, Zehui Xiong, Hongyang Du +2
The burgeoning generative artificial intelligence technology offers novel insights into the development of semantic communication (SemCom) frameworks. These frameworks hold the pot…
Joint User Association and Resource Pricing for Metaverse: Distributed and Centralized Approaches
Xumin Huang, Weifeng Zhong, Jiangtian Nie +4
Metaverse as the next-generation Internet provides users with physical-virtual world interactions. To improve the quality of immersive experience, users access to Metaverse service…