most citedDeep progressive reinforcement learning-based flexible resource scheduling framework for IRS and UAV-assisted MEC system

47 citations · 59 across the 7 of their papers we have counts for

collaborators

7 papers

cs.IT20251 cited

Lightweight Vision Model-based Multi-user Semantic Communication Systems

Feibo Jiang, Siwei Tu, Li Dong +5

Semantic Communication (SemCom) is a promising new paradigm for next-generation communication systems, emphasizing the transmission of core information, particularly in environment…

cs.IT20251 cited

M4SC: An MLLM-based Multi-modal, Multi-task and Multi-user Semantic Communication System

Feibo Jiang, Siwei Tu, Li Dong +3

Multi-modal Large Language Models (MLLMs) are capable of precisely extracting high-level semantic information from multi-modal data, enabling multi-task understanding and generatio…

cs.LG20247 cited

Explainable Semantic Federated Learning Enabled Industrial Edge Network for Fire Surveillance

Li Dong, Yubo Peng, Feibo Jiang +2

In fire surveillance, Industrial Internet of Things (IIoT) devices require transmitting large monitoring data frequently, which leads to huge consumption of spectrum resources. Hen…

cs.IT2024

Large Generative Model-assisted Talking-face Semantic Communication System

Feibo Jiang, Siwei Tu, Li Dong +3

The rapid development of generative Artificial Intelligence (AI) continually unveils the potential of Semantic Communication (SemCom). However, current talking-face SemCom systems…

cs.LG202447 cited

Deep progressive reinforcement learning-based flexible resource scheduling framework for IRS and UAV-assisted MEC system

Li Dong, Feibo Jiang, Minjie Wang +2

The intelligent reflection surface (IRS) and unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system is widely used in temporary and emergency scenarios. Our goal…

cs.CV2024

Visual Language Model based Cross-modal Semantic Communication Systems

Feibo Jiang, Chuanguo Tang, Li Dong +3

Semantic Communication (SC) has emerged as a novel communication paradigm in recent years, successfully transcending the Shannon physical capacity limits through innovative semanti…