DRL-Driven Dynamic Resource Allocation for Task-Oriented Semantic Communication-Reference-Cited by-同舟云学术

DRL-Driven Dynamic Resource Allocation for Task-Oriented Semantic Communication

Published:2023-07 Issue:7 Volume:71 Page:3992-4004
ISSN:0090-6778
Container-title:IEEE Transactions on Communications
language:
Short-container-title:IEEE Trans. Commun.

Author:

Zhang Haijun¹^ORCID,Wang Hongyu¹^ORCID,Li Yabo¹^ORCID,Long Keping¹^ORCID,Nallanathan Arumugam²^ORCID

Affiliation:

1. Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services, and the Beijing Advanced Innovation Center for Material Genome Engineering, University of Science and Technology Beijing, Beijing, China

2. School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Beijing Natural Science Foundation

Xiaomi Fund of Young Scholar, and China University Industry-University-Research Collaborative Innovation Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/26/10184153/10122232.pdf?arnumber=10122232

Reference32 articles.

1. Streaming Video QoE Modeling and Prediction: A Long Short-Term Memory Approach

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4. Access Control and Resource Allocation for M2M Communications in Industrial Automation

5. Deep Reinforcement Learning Based Multidimensional Resource Management for Energy Harvesting Cognitive NOMA Communications

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