777 citations · 1.1k across the 20 of their papers we have counts for
20 papers
Large Language Model Empowered CSI Feedback in Massive MIMO Systems
Jie Wu, Wei Xu, Le Liang +2
Despite the success of large language models (LLMs) across domains, their potential for efficient channel state information (CSI) compression and feedback in frequency division dup…
Meta-Learning Empowered Graph Neural Networks for Radio Resource Management
Kai Huang, Le Liang, Xinping Yi +3
In this paper, we consider a radio resource management (RRM) problem in the dynamic wireless networks, comprising multiple communication links that share the same spectrum resource…
Meta Reinforcement Learning for Fast Spectrum Sharing in Vehicular Networks
Kai Huang, Le Liang, Shi Jin +1
In this paper, we investigate the problem of fast spectrum sharing in vehicle-to-everything communication. In order to improve the spectrum efficiency of the whole system, the spec…
SAFARI: Sparsity enabled Federated Learning with Limited and Unreliable Communications
Yuzhu Mao, Zihao Zhao, Meilin Yang +5
Federated learning (FL) enables edge devices to collaboratively learn a model in a distributed fashion. Many existing researches have focused on improving communication efficiency…
Reinforcement Learning Based Power Control for Reliable Mission-Critical Wireless Transmission
Chongtao Guo, Zhengchao Li, Le Liang +1
In this paper, we investigate sequential power allocation over fast varying channels for mission-critical applications, aiming to minimize the expected sum power while guaranteeing…
Decentralized Federated Learning with Unreliable Communications
Hao Ye, Le Liang, Geoffrey Li
Decentralized federated learning, inherited from decentralized learning, enables the edge devices to collaborate on model training in a peer-to-peer manner without the assistance o…