A Hybrid Optimization and Deep RL Approach for Resource Allocation in Semi-GF NOMA Networks-Reference-Cited by-同舟云学术

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A Hybrid Optimization and Deep RL Approach for Resource Allocation in Semi-GF NOMA Networks

Published:2023-09-05 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 34th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)
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Author:

Tran Duc-Dung¹,Ha Vu Nguyen¹,Chatzinotas Symeon¹,Nguyen Ti Ti²

Affiliation:

1. University of Luxembourg,Interdisciplinary Centre for Security, Reliability and Trust (SnT),Luxembourg

2. Université du Québec,Montréal,Canada

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10293227/10293746/10293810.pdf?arnumber=10293810

Reference22 articles.

1. Multi-Agent DRL Approach for Energy-Efficient Resource Allocation in URLLC-Enabled Grant-Free NOMA Systems

2. Deep Reinforcement Learning-Based Grant-Free NOMA Optimization for mURLLC

3. Energy-Efficient Short Packet Communications for Uplink NOMA-Based Massive MTC Networks

4. Admission Control and Network Slicing for Multi-Numerology 5G Wireless Networks

5. Energy-Efficient Hybrid Precoding for mmWave Multi-User Systems

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Reinforcement Learning for QoE-Oriented Flexible Bandwidth Allocation in Satellite Communication Networks;2023 IEEE Globecom Workshops (GC Wkshps);2023-12-04

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