9 papers
Generalizable and Computational Efficient Channel Extrapolation for 6G: A Configurable AI-Driven Framework Built from a Modular Perspective
Yuan Gao, Xinyi Wu, Jiang Jun +5
Acquiring channel state information (CSI) with manageable overhead has been essential to provide high-performance communication services, which is extremely challenging in the emer…
Networking-Aware Energy Efficiency in Agentic AI Inference: A Survey
Xiaojing Chen, Haiqi Yu, Wei Ni +5
The rapid emergence of Large Language Models (LLMs) has catalyzed Agentic artificial intelligence (AI), autonomous systems integrating perception, reasoning, and action into closed…
A Unified QoS-Aware Multiplexing Framework for Next Generation Immersive Communication with Legacy Wireless Applications
Jihong Li, Shunqing Zhang, Tao Yu +7
Immersive communication, including emerging augmented reality, virtual reality, and holographic telepresence, has been identified as a key service for enabling next-generation wire…
Energy Optimization of Multi-task DNN Inference in MEC-assisted XR Devices: A Lyapunov-Guided Reinforcement Learning Approach
Yanzan Sun, Jiacheng Qiu, Guangjin Pan +4
Extended reality (XR), blending virtual and real worlds, is a key application of future networks. While AI advancements enhance XR capabilities, they also impose significant comput…
Towards Dynamic Resource Allocation and Client Scheduling in Hierarchical Federated Learning: A Two-Phase Deep Reinforcement Learning Approach
Xiaojing Chen, Zhenyuan Li, Wei Ni +5
Federated learning (FL) is a viable technique to train a shared machine learning model without sharing data. Hierarchical FL (HFL) system has yet to be studied regrading its multip…
IREE Oriented Green 6G Networks: A Radial Basis Function Based Approach
Tao Yu, Pengbo Huang, Shunqing Zhang +3
In order to provide design guidelines for energy efficient 6G networks, we propose a novel radial basis function (RBF) based optimization framework to maximize the integrated relat…