66 citations · 73 across the 4 of their papers we have counts for
4 papers
Collaborative Computing in Non-Terrestrial Networks: A Multi-Time-Scale Deep Reinforcement Learning Approach
Yang Cao, Shao-Yu Lien, Ying-Chang Liang +3
Constructing earth-fixed cells with low-earth orbit (LEO) satellites in non-terrestrial networks (NTNs) has been the most promising paradigm to enable global coverage. The limited…
Collaborative Deep Reinforcement Learning for Resource Optimization in Non-Terrestrial Networks
Yang Cao, Shao-Yu Lien, Ying-Chang Liang +3
Non-terrestrial networks (NTNs) with low-earth orbit (LEO) satellites have been regarded as promising remedies to support global ubiquitous wireless services. Due to the rapid mobi…
Deep Learning-Empowered Semantic Communication Systems with a Shared Knowledge Base
Peng Yi, Yang Cao, Xin Kang +1
Deep learning-empowered semantic communication is regarded as a promising candidate for future 6G networks. Although existing semantic communication systems have achieved superior…
Integrated Distributed Semantic Communication and Over-the-air Computation for Cooperative Spectrum Sensing
Peng Yi, Yang Cao, Xin Kang +1
Cooperative spectrum sensing (CSS) is a promising approach to improve the detection of primary users (PUs) using multiple sensors. However, there are several challenges for existin…