Model-Based Reinforcement Learning With Kernels for Resource Allocation in RAN Slices

Author:

Alcaraz Juan J.1ORCID,Losilla Fernando1ORCID,Zanella Andrea2ORCID,Zorzi Michele2ORCID

Affiliation:

1. Department of Information Technologies and Communications, Technical University of Cartagena, Cartagena, Spain

2. Department of Information Engineering, University of Padova, Padova, Italy

Funder

Ministerio de Ciencia e Innovaci?n

Ministerio de Educaci?n y Formaci?n Profesional

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Flexible RAN Slicing in Open RAN With Constrained Multi-Agent Reinforcement Learning;IEEE Journal on Selected Areas in Communications;2024-02

2. Hierarchical Reinforcement Learning Based Resource Allocation for RAN Slicing;IEEE Access;2024

3. An auction-based distributed network slicing scheme for resource allocation in satellite-UAV integrated networks;Computer Communications;2023-10

4. Design and Implementation of Mini Programs that Integrate Foreign Trade English Video Learning Resources;2023 International Conference on Network, Multimedia and Information Technology (NMITCON);2023-09-01

5. Intent-Driven RAN Slice Orchestration: A Multi-Agent Deep Reinforcement Learning Based Approach;2023 IEEE/CIC International Conference on Communications in China (ICCC Workshops);2023-08-10

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