14 papers
LLM-hRIC: LLM-empowered Hierarchical RAN Intelligent Control for O-RAN
Lingyan Bao, Sinwoong Yun, Jemin Lee +1
Despite recent advances in applying large language models (LLMs) and machine learning (ML) techniques to open radio access network (O-RAN), critical challenges remain, such as insu…
Federated Learning Resilient to Byzantine Attacks and Data Heterogeneity
Shiyuan Zuo, Xingrun Yan, Rongfei Fan +4
This paper addresses federated learning (FL) in the context of malicious Byzantine attacks and data heterogeneity. We introduce a novel Robust Average Gradient Algorithm (RAGA), wh…
Distributed Gossip-GAN for Low-overhead CSI Feedback Training in FDD mMIMO-OFDM Systems
Yuwen Cao, Guijun Liu, Tomoaki Ohtsuki +2
The deep autoencoder (DAE) framework has turned out to be efficient in reducing the channel state information (CSI) feedback overhead in massive multiple-input multipleoutput (mMIM…
Integrated user scheduling and beam steering in over-the-air federated learning for mobile IoT
Shengheng Liu, Ningning Fu, Zhonghao Zhang +2
The rising popularity of Internet of things (IoT) has spurred technological advancements in mobile internet and interconnected systems. While offering flexible connectivity and int…
Diffusion-Driven Semantic Communication for Generative Models with Bandwidth Constraints
Lei Guo, Wei Chen, Yuxuan Sun +3
Diffusion models have been extensively utilized in AI-generated content (AIGC) in recent years, thanks to the superior generation capabilities. Combining with semantic communicatio…
Lightweight Task-Oriented Semantic Communication Empowered by Large-Scale AI Models
Chuanhong Liu, Caili Guo, Yang Yang +2
Recent studies have focused on leveraging large-scale artificial intelligence (LAI) models to improve semantic representation and compression capabilities. However, the substantial…