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Celimuge Wu

Researcher at University of Electro-Communications

Publications -  186
Citations -  4661

Celimuge Wu is an academic researcher from University of Electro-Communications. The author has contributed to research in topics: Vehicular ad hoc network & Wireless ad hoc network. The author has an hindex of 29, co-authored 186 publications receiving 2544 citations. Previous affiliations of Celimuge Wu include Beijing Institute of Technology.

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Optimized Computation Offloading Performance in Virtual Edge Computing Systems Via Deep Reinforcement Learning

TL;DR: This paper considers MEC for a representative mobile user in an ultradense sliced RAN, where multiple base stations are available to be selected for computation offloading and proposes a double deep ${Q}$ -network (DQN)-based strategic computation offload algorithm to learn the optimal policy without knowing a priori knowledge of network dynamics.
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AVE: Autonomous Vehicular Edge Computing Framework with ACO-Based Scheduling

TL;DR: Efficient job caching is proposed to better schedule jobs based on the information collected on neighboring vehicles, including GPS information, and a scheduling algorithm based on ant colony optimization is designed to solve this job assignment problem.
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Edge Computing in 5G: A Review

TL;DR: A taxonomy of edge computing in 5G is established, which gives an overview of existing state-of-the-art solutions of edge Computing in5G on the basis of objectives, computational platforms, attributes, 5G functions, performance measures, and roles.
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QoS-Guarantee Resource Allocation for Multibeam Satellite Industrial Internet of Things With NOMA

TL;DR: A multibeam satellite IIoT in Ka-band is proposed to realize wide-area coverage and long-distance transmissions, which uses nonorthogonal multiple access (NOMA) for each beam to improve transmission rate.
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Federated Learning for Vehicular Internet of Things: Recent Advances and Open Issues

TL;DR: The significance and technical challenges of applying FL in vehicular IoT, and future research directions are discussed, and a brief survey of existing studies on FL and its use in wireless IoT is conducted.