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Found 8 papers, 3 papers with code
WirelessAgent: Large Language Model Agents for Intelligent Wireless Networks
We demonstrate the effectiveness of WirelessAgent through a comprehensive case study on network slicing.
Neural Representation for Wireless Radiation Field Reconstruction: A 3D Gaussian Splatting Approach
Nevertheless, developing an effective channel modeling approach has been a long-standing challenge.
WirelessAgent: Large Language Model Agents for Intelligent Wireless Networks
Wireless networks are increasingly facing challenges due to their expanding scale and complexity.
A Federated Online Restless Bandit Framework for Cooperative Resource Allocation
In this paper, we study the cooperative resource allocation problem with unknown system dynamics of MRPs.
Two-Stage Resource Allocation in Reconfigurable Intelligent Surface Assisted Hybrid Networks via Multi-Player Bandits
This paper considers a resource allocation problem where several Internet-of-Things (IoT) devices send data to a base station (BS) with or without the help of the reconfigurable intelligent surface (RIS) assisted cellular network.
WirelessLLM: Empowering Large Language Models Towards Wireless Intelligence
To empower LLMs with knowledge and expertise in the wireless domain, this paper proposes WirelessLLM, a comprehensive framework for adapting and enhancing LLMs to address the unique challenges and requirements of wireless communication networks.
Data-Driven Online Resource Allocation for User Experience Improvement in Mobile Edge Clouds
Due to the learned objective model is typically non-convex and challenging to solve in real-time, we leverage the Lyapunov optimization to decouple the long-term average constraint and apply the prime-dual method to solve this decoupled resource allocation problem.
From Learning to Analytics: Improving Model Efficacy with Goal-Directed Client Selection
To address the challenges posed by system and data heterogeneities in the FL process, we study a goal-directed client selection problem based on the model analytics framework by selecting a subset of clients for the model training.
