Task offloading and resource allocation in NOMA-VEC: A multi-agent deep graph reinforcement learning algorithm

Vehicular edge computing (VEC) is emerging as a promising solution paradigm to meet the requirements of compute-intensive applications in internet of vehicle (IoV). Non-orthogonal multiple access (NOMA) has advantages in improving spectrum efficiency and dealing with bandwidth scarcity and cost. It...

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Veröffentlicht in:	China communications Jg. 21; H. 8; S. 79 - 88
Hauptverfasser:	Yonghui, Hu, Zuodong, Jin, Peng, Qi, Dan, Tao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	China Institute of Communications 01.08.2024 School of Electronic and Information Engineering,Beijing Jiaotong University,Beijing 100044,China
Schlagworte:	Costs edge computing Feature extraction graph convolutional network Interference NOMA Optimization reinforcement learning Resource management Servers task offloading graph convolutional net-work task offloading edge computing reinforcement learning
ISSN:	1673-5447
Online-Zugang:	Volltext
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