collaborators

8 papers

cs.NI2026

Adaptive Personalized Federated Reinforcement Learning for RIS-Assisted Aerial Relays in SAGINs with Fluid Antennas

Yuxuan Yang, Bin Lyu, Abbas Jamalipour

Space-air-ground integrated networks (SAGINs) interconnect satellites, uncrewed aerial vehicles (UAVs), and ground devices to enable flexible and ubiquitous wireless services. The…

cs.NI2026

Selfish Cooperation Towards Low-Altitude Economy: Integrated Multi-Service Deployment with Resilient Federated Reinforcement Learning

Yuxuan Yang, Bin Lyu, Abbas Jamalipour

The low-altitude economy (LAE) is a rapidly emerging paradigm that builds a service-centric economic ecosystem through large-scale and sustainable uncrewed aerial vehicle (UAV)-ena…

cs.NI2026

Federated Agentic AI for Wireless Networks: Fundamentals, Approaches, and Applications

Lingyi Cai, Yu Zhang, Ruichen Zhang +5

Agentic artificial intelligence (AI) presents a promising pathway toward realizing autonomous and self-improving wireless network services. However, resource-constrained, widely di…

eess.SP2025

Agentic Graph Neural Networks for Wireless Communications and Networking Towards Edge General Intelligence: A Survey

Yang Lu, Shengli Zhang, Chang Liu +6

The rapid advancement of communication technologies has driven the evolution of communication networks towards both high-dimensional resource utilization and multifunctional integr…

cs.CR2025

Zero-Trust Foundation Models: A New Paradigm for Secure and Collaborative Artificial Intelligence for Internet of Things

Kai Li, Conggai Li, Xin Yuan +8

This paper focuses on Zero-Trust Foundation Models (ZTFMs), a novel paradigm that embeds zero-trust security principles into the lifecycle of foundation models (FMs) for Internet o…

cs.LG2025

LAPA-based Dynamic Privacy Optimization for Wireless Federated Learning in Heterogeneous Environments

Pengcheng Sun, Erwu Liu, Wei Ni +4

Federated Learning (FL) is a distributed machine learning paradigm based on protecting data privacy of devices, which however, can still be broken by gradient leakage attack via pa…