Online Computation Offloading in NOMA-Based Multi-Access Edge Computing: A Deep Reinforcement Learning Approach
One of the missions of fifth generation (5G) wireless networks is to provide massive connectivity of the fast growing number of Internet of Things (IoT) devices. To satisfy this mission, non-orthogonal multiple access (NOMA) has been recognized as a promising solution for 5G networks to significantl...
Main Authors: | Maurice Nduwayezu, Quoc-Viet Pham, Won-Joo Hwang |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9102308/ |
Similar Items
-
Joint Computational Offloading and Data-Content Caching in NOMA-MEC Networks
by: Luan N. T. Huynh, et al.
Published: (2021-01-01) -
Multi-Access Edge Computing Empowered Heterogeneous Networks: A Novel Architecture and Potential Works
by: June-Woo Ryu, et al.
Published: (2019-07-01) -
DRL-Assisted Resource Allocation for NOMA-MEC Offloading with Hybrid SIC
by: Haodong Li, et al.
Published: (2021-05-01) -
Energy-Aware User Association for NOMA-Based Mobile Edge Computing Using Matching-Coalition Game
by: Chen Xu, et al.
Published: (2020-01-01) -
Joint Offloading Decision and Resource Allocation for Multiuser NOMA-MEC Systems
by: Wen'An Zhou, et al.
Published: (2019-01-01)