D2D Resource Allocation Based on Reinforcement Learning and QoS

Fang‐Chang Kuo; Hwang-Cheng Wang; Chih‐Cheng Tseng; Jung-Shyr Wu; Jiahao Xu; Jieh-Ren Chang

doi:10.1007/s11036-023-02145-3

ScienceGate Book Chapters

JOURNAL ARTICLE

D2D Resource Allocation Based on Reinforcement Learning and QoS

Fang‐Chang Kuo Hwang-Cheng Wang Chih‐Cheng Tseng Jung-Shyr Wu Jiahao Xu Jieh-Ren Chang

Year: 2023 Journal: Mobile Networks and Applications Vol: 28 (3)Pages: 1076-1095 Publisher: Springer Science+Business Media

DOI: 10.1007/s11036-023-02145-3

Get Full-Text PDF Get Analytical Report

Keywords:

Computer science Reinforcement learning Scheme (mathematics) Resource allocation Computer network Reuse Cellular network Wireless network Wireless Quality of service Distributed computing Artificial intelligence Telecommunications

Metrics

Cited By

0.17

FWCI (Field Weighted Citation Impact)

Refs

0.43

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Advanced MIMO Systems Optimization

Physical Sciences → Engineering → Electrical and Electronic Engineering

Cognitive Radio Networks and Spectrum Sensing

Physical Sciences → Computer Science → Computer Networks and Communications

Age of Information Optimization

Physical Sciences → Computer Science → Computer Networks and Communications

D2D Resource Allocation Based on Reinforcement Learning and QoS

Metrics

Citation History

Topics

Related Documents

Reinforcement-learning-based wireless resource allocation

Deep Reinforcement Learning based Resource Allocation in NOMA

Aircraft Resource Allocation Based on Deep Reinforcement Learning

Reinforcement Learning-Based Resource Allocation in Fog Networks

Deep Reinforcement Learning Based Resource Allocation for LoRaWAN