8 papers
FedCC: Towards Addressing Label Distribution Skews in Distillation-Based Federated Learning
Wenxuan Ye, Onur Ayan, Xueli An +1
Federated Learning (FL) enables distributed clients to collaboratively train models without sharing raw data, making it promising for leveraging massive devices in communication ne…
Tool Use as Action: Towards Agentic Control in Mobile Core Networks
Purna Sai Garigipati, Onur Ayan, Kishor Chandra Joshi +1
Artificial Intelligence (AI) will play an essential role in 6G. It will fundamentally reshape the network architecture itself and drive major changes in the design of network entit…
Beyond State Machines: Executing Network Procedures with Agentic Tool-Calling Sequences
Purna Sai Garigipati, Onur Ayan, Kishor Chandra Joshi +1
Agentic AI will be an essential enabling technology for designing future mobile communication systems, which could provide flexible and customized services, automate complex networ…
Customized User Plane Processing via Code Generating AI Agents for Next Generation Mobile Networks
Xiaowen Ma, Onur Ayan, Yunpu Ma +1
Generative AI is envisioned to have a crucial impact on next generation mobile networking, making the sixth generation (6G) system considerably more autonomous, flexible, and adapt…
Towards a Larger Model via One-Shot Federated Learning on Heterogeneous Client Models
Wenxuan Ye, Xueli An, Onur Ayan +3
Large models, renowned for superior performance, outperform smaller ones even without billion-parameter scales. While mobile network servers have ample computational resources to s…
Age-Aware CSI Acquisition of a Finite-State Markovian Channel
Onur Ayan, Jiping Luo, Xueli An +1
The Age of Information (AoI) has emerged as a critical metric for quantifying information freshness; however, its interplay with channel estimation in partially observable wireless…