Deep-Reinforcement-Learning-Based Resource Allocation for MEC-Assisted Satellite–Terrestrial Integrated Networks

Fangfang Yin; Qihong Liu; Danpu Liu; Libiao Jin; Shufeng Li

doi:10.1109/jiot.2025.3628965

ScienceGate Book Chapters

JOURNAL ARTICLE

Deep-Reinforcement-Learning-Based Resource Allocation for MEC-Assisted Satellite–Terrestrial Integrated Networks

Fangfang Yin Qihong Liu Danpu Liu Libiao Jin Shufeng Li

Year: 2025 Journal: IEEE Internet of Things Journal Vol: 13 (1)Pages: 1440-1459 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/jiot.2025.3628965

Get Full-Text PDF Get Analytical Report

Keywords:

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Deep-Reinforcement-Learning-Based Resource Allocation for MEC-Assisted Satellite–Terrestrial Integrated Networks

Metrics

Topics

Related Documents

Deep Reinforcement Learning‐Based Joint Satellite Scheduling and Resource Allocation in Satellite‐Terrestrial Integrated Networks

Deep Reinforcement Learning for Computation Offloading and Resource Allocation in Satellite-Terrestrial Integrated Networks

Deep Reinforcement Learning-Based Resource Allocation for RSMA in LEO Satellite-Terrestrial Networks

Computation Offloading and Resource Allocation in Satellite-Terrestrial Integrated Networks: A Deep Reinforcement Learning Approach

QoS-Guarantee Resource Allocation of Slicing Services in Integrated Satellite-Terrestrial Networks Based on Deep Reinforcement Learning