数字孪生加速在线深度强化学习用于分片通信网络中的接纳控制

IF 7.2 2区计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Transactions on Communications Pub Date : 2024-10-09 DOI:10.1109/tcomm.2024.3476430

Zhenyu Tao, Wei Xu, Xiaohu You

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Digital Twin-Accelerated Online Deep Reinforcement Learning for Admission Control in Sliced Communication Networks

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来源期刊

IEEE Transactions on Communications 工程技术-电信学

CiteScore

16.10

自引率

8.40%

发文量

528

审稿时长

4.1 months

期刊介绍： The IEEE Transactions on Communications is dedicated to publishing high-quality manuscripts that showcase advancements in the state-of-the-art of telecommunications. Our scope encompasses all aspects of telecommunications, including telephone, telegraphy, facsimile, and television, facilitated by electromagnetic propagation methods such as radio, wire, aerial, underground, coaxial, and submarine cables, as well as waveguides, communication satellites, and lasers. We cover telecommunications in various settings, including marine, aeronautical, space, and fixed station services, addressing topics such as repeaters, radio relaying, signal storage, regeneration, error detection and correction, multiplexing, carrier techniques, communication switching systems, data communications, and communication theory. Join us in advancing the field of telecommunications through groundbreaking research and innovation.