3 citations · 8 across the 11 of their papers we have counts for
11 papers
Wireless Personal Agent: Extending Wireless Intelligence from Networks to Terminals
Jiedan Tan, Fang Liu, Jingwen Tong +3
Wireless networks are evolving from connectivity-oriented infrastructures into intelligent and personalized service platforms. Existing wireless intelligence remains centered on ne…
WirelessBench: A Tolerance-Aware LLM Agent Benchmark for Wireless Network Intelligence
Jingwen Tong, Fang Liu, Linkai Xv +6
LLM agents are emerging as a key enabler for autonomous wireless network management. Reliably deploying them, however, demands benchmarks that reflect real engineering risk. Existi…
Intelligent Channel Allocation for IEEE 802.11be Multi-Link Operation: When MAB Meets LLM
Shumin Lian, Jingwen Tong, Jun Zhang +1
WiFi networks have achieved remarkable success in enabling seamless communication and data exchange worldwide. The IEEE 802.11be standard, known as WiFi 7, introduces Multi-Link Op…
WirelessAgent: Large Language Model Agents for Intelligent Wireless Networks
Jingwen Tong, Wei Guo, Jiawei Shao +4
The rapid evolution of wireless networks presents unprecedented challenges in managing complex and dynamic systems. Existing methods are increasingly facing fundamental limitations…
LLM-Slice: Dedicated Wireless Network Slicing for Large Language Models
Boyi Liu, Jingwen Tong, Jun Zhang
The rapid adoption of large language models (LLMs) presents new challenges for existing network architectures due to significant peak traffic and high communication uncertainty. Tr…
WirelessAgent: Large Language Model Agents for Intelligent Wireless Networks
Jingwen Tong, Jiawei Shao, Qiong Wu +4
Wireless networks are increasingly facing challenges due to their expanding scale and complexity. These challenges underscore the need for advanced AI-driven strategies, particular…
WirelessLLM: Empowering Large Language Models Towards Wireless Intelligence
Jiawei Shao, Jingwen Tong, Qiong Wu +4
The rapid evolution of wireless technologies and the growing complexity of network infrastructures necessitate a paradigm shift in how communication networks are designed, configur…
A Federated Online Restless Bandit Framework for Cooperative Resource Allocation
Jingwen Tong, Xinran Li, Liqun Fu +2
Restless multi-armed bandits (RMABs) have been widely utilized to address resource allocation problems with Markov reward processes (MRPs). Existing works often assume that the dyn…
EdgeLoc: A Communication-Adaptive Parallel System for Real-Time Localization in Infrastructure-Assisted Autonomous Driving
Boyi Liu, Jingwen Tong, Yufan Zhuang
This paper presents EdgeLoc, an infrastructure-assisted, real-time localization system for autonomous driving that addresses the incompatibility between traditional localization me…
Data-Driven Online Resource Allocation for User Experience Improvement in Mobile Edge Clouds
Liqun Fu, Jingwen Tong, Tongtong Lin +1
As the cloud is pushed to the edge of the network, resource allocation for user experience improvement in mobile edge clouds (MEC) is increasingly important and faces multiple chal…
From Learning to Analytics: Improving Model Efficacy with Goal-Directed Client Selection
Jingwen Tong, Zhenzhen Chen, Liqun Fu +2
Federated learning (FL) is an appealing paradigm for learning a global model among distributed clients while preserving data privacy. Driven by the demand for high-quality user exp…