B
Bo Yang
Researcher at Singapore University of Technology and Design
Publications - 57
Citations - 970
Bo Yang is an academic researcher from Singapore University of Technology and Design. The author has contributed to research in topics: Throughput & Communication channel. The author has an hindex of 11, co-authored 57 publications receiving 384 citations. Previous affiliations of Bo Yang include Northwestern Polytechnical University & Prairie View A&M University.
Papers
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Journal ArticleDOI
Computation Offloading in Multi-Access Edge Computing: A Multi-Task Learning Approach
TL;DR: A novel offloading framework for the multi-server MEC network where each AP is equipped with an MES assisting mobile users (MUs) in executing computation-intensive jobs via offloading is proposed.
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Offloading Optimization in Edge Computing for Deep-Learning-Enabled Target Tracking by Internet of UAVs
TL;DR: A novel hierarchical DL tasks distribution framework is proposed, where the UAV is embedded with lower layers of the pretrained CNN model while the MEC server (MES) with rich computing resources will handle the higher levels of the CNN model.
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Mobile-Edge-Computing-Based Hierarchical Machine Learning Tasks Distribution for IIoT
TL;DR: In this article, a novel framework of mobile edge computing (MEC)-based hierarchical machine learning (ML) tasks distribution for the Industrial Internet of Things is proposed and an optimal offloading strategy selection algorithm is proposed.
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Reconfigurable Intelligent Surface-Assisted Aerial-Terrestrial Communications via Multi-Task Learning
TL;DR: This paper designs an adaptive RIS-assisted transmission protocol, in which the channel estimation, transmission strategy, and data transmission are independently implemented in a frame to maximize the overall system throughput and reduce the transmit power.
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A Machine Learning Enabled MAC Framework for Heterogeneous Internet-of-Things Networks
TL;DR: This paper presents a distributed MAC framework assisted by machine learning for the Heterogeneous IoT system, where the IoT devices coexist with the WiFi users in the unlicensed industrial, scientific, and medical spectrum.