Adapting to Dynamic LEO-B5G Systems: Meta-Critic Learning Based Efficient Resource Scheduling-Reference-Cited by-同舟云学术

Adapting to Dynamic LEO-B5G Systems: Meta-Critic Learning Based Efficient Resource Scheduling

Author:

Yuan Yaxiong¹^ORCID,Lei Lei²^ORCID,Vu Thang X.¹^ORCID,Chang Zheng³^ORCID,Chatzinotas Symeon¹^ORCID,Sun Sumei⁴^ORCID

Affiliation:

1. Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, Kirchberg, Luxembourg

2. School of Information and Communications Engineering, Xi’an Jiaotong University, Xi’an, China

3. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China

4. Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore

Funder

European Research Council (ERC) Project Actively Enhanced Cognition based Framework for Design of Complex Systems

Luxembourg National Research Fund (FNR) CORE projects: Leveraging AI to Empower the Next Generation of Satellite Communications

Resource Optimization for integrated Satellite-5G nETworks with non-orThogonal multiple Access

Resource Optimization for Next Generation of Flexible SATellite Payloads

SmartSpace

FNR Bilateral Project Learning-Assisted Optimization for Resource and Security Management in Slicing-Based 5G Networks

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications

Link

Reference45 articles.

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